突变控制技术及其应用研究
|
摘要
目前世界各国许多学者都在致力探索非线性控制问题的解决方法。控制系统的非线性控制规律研究是当今自控理论学界重点研究的课题之一。本论文将致力于探索一种新的控制理论及其应用方法，即将突变理论引入到控制系统中，形成突变控制的一些理论方法。并将突变控制机制的研究应用于一些特殊控制场合。
本文从研究系统的突变现象入手，将突变理论引入到系统的分析与控制中，使之与控制理论相结合，并提出一个新的概念——突变控制理论，进而研究突变控制的技术方法及其在人工心脏控制系统和导航系统中的应用。
人工心脏是彻底解决心肌坏死性疾病的主要途径，但是目前世界上还未研究出能够全部植入人体的有效替代原有心脏功能的人工心脏(简称全植入式人工心脏)。可以说，控制将是全植入式人工心脏的关键技术之一，而人工心脏的控制决不是简单的线性控制或常规的非线性控制。因此，本论文所研究的具有突变机制的控制系统将有助于推动全植入式人工心脏的进展。
突变控制模型就是针对具有突变特征非线性系统而提出的，也可以说是从一个全新的角度对某些非线性控制系统解决方案的一种探索。
将突变理论与控制技术相结合，首次提出了突变控制技术的概念。对于具有突变机制的系统进行了较为深入的研究，并给出了突变控制解决方案，以便实现有效控制。突变在于系统状态的突然改变，状态的改变不只是有快、慢之分，更主要是分析其变化的模式和规律。系统突变有其原因(包括内因和外因)，系统突变的内因是系统运行到一定阶段或状态而自然发生的；系统突变的外因是系统在运行时受到外界的干扰而发生的。系统状态发生突变的现象是存在的，但是以往很少对其突变特性进行研究。当系统中的信息在某一阶段呈现突变状态时，根据其突变特点及归属类型引入不同的势函数模型。将势函数方程引入到控制系统的建模，就可以对系统的变化进行定量描述。本论文就是利用突变理论研究控制系统的突变特性，并提出突变控制模型以描述系统状态变化的规律。突变势函数被引入控制系统，首次提出了突变控制模型；设计了突变预测模型，并将其应用于有关控制系统中。
’
哈尔滨工程人学博士学位论文
人工心脏的控制既属于工程控制论范畴，也属于主物控制论范畴。在对
大量B型超声心动图和ECT图象实验的基础上，建立了人体心脏运动模型，
首次设计了全植入式人工心脏控制系统的突变控制模型。突变控制模型的研
究是将突变理论引入到控制理论中的重要一步，也可以说是两种理论的结合
点，很有可能成为今后研究新的突变控制理论的基础。主于人体心脏运动具
有突变性质，所以为了使人工心脏能够逼近真实心脏的运动过程，那么其控
制系统中就应具有突变控制模型。因此，对于突变控制模型的研究具有较为
重要的理论意义和实际应用价值。
针对舰艇战斗航海需要，将突变控制技术应用到惯性组合导航系统中，
首次设计了导航控制系统应急状态突变控制模型，突变故障诊断模型c
Now many scholars are all at concentrate on the search of the problem of nonlinear control. The nonlinear control of the control system of the law research is one of the lessons that study nowadays in automatic control theory educational circles. This article will be on the foundation work to search a new control theory and the the application of it. That is apply the catastrophe theory to control system , formulating some theories of catastrophe control. The research will put control mechanism in the some and special control occasion. The catastrophe phenomena would be the entry of the problem that will be settled in this article. It will be taken into the analysis and the control of the system, to combine the catastrophe theory with automatic control theory. So we can propose a new concept that is catastrophe control theory. We try the theory to the control system of total artificial heart.
The artificial heart is nowadays more popular in the developed countries such as in the United States, England and so on. They are so concentrated on the availability of artificial heart, it thoroughly clinch the myocardial the critical path of bad dead paroxysm, but the present world is up to now still not bring the prototype that can be all transplanted into the human body to replace function of originally heart(total artificial heart). We can say, and it will be that the key technicality of transplant the artificial heart's lies on control system, but the artificial heart never is the nonlinear control of the simple distribution control or routine. Control system in thesis which is studied about the control system with the catastrophe mechanism will be beneficial to push the holoenzymes to transplant the quinonoid formula artificial the heart's progress.
The model of catastrophe control system is to aim at to the characteristic of nonlinear system and suggested, as well to be from the solution of some nonlinear control systems of an all new angle paraquinones of such kind search.
Combine together the catastrophe theory and control technique, and proposed the technical notion of catastrophe control for the first time. Having done many deep research on the mechanism of catastrophe, giving the solution of the control of catastrophe, to reach the effective control. The catastrophe consists in the much more than only possession of the alteration of the system status alteration, not on the change speed status quick, slow bat batch. The system catastrophe has its own reason (include the inside but also outside). The inside reason happen when system run more naturally, and the outside reason is that outsider interference but occurrence. The phenomena that system status change are very common, but
former few as to it's the catastrophe characteristic steer the research. The article is a take advantages of catastrophe theory research the catastrophe characteristic, and the law of status change of catastrophe control system. Design catastrophe predication form, apply its model into the appliance which is in the in reference to control system under catastrophe the first time.
The control of the artificial heart since is in the category of the engineering control theory, and as well in the category of biological control theory. On the base of having studied with many B mode ultrasound cardiograph}' and ECT image experimenting, create model of human body heart moving, first time design the model total artificial heart of catastrophe control. Research of the model of catastrophe control introduce the catastrophe theory into the control system theory . it is the first step, and as well to could be the combination of the two theory and it will be the basic study of future catastrophe control theory.
Aim at the fleet combat the navigation requirement, will introduce the catastrophe control technique into the integrated navigation system, first time design navigate control system for meeting the need of the navigation of ship, use the model of control under catastrophe theory into integrated navigation. Design the model of catastro
本文从研究系统的突变现象入手，将突变理论引入到系统的分析与控制中，使之与控制理论相结合，并提出一个新的概念——突变控制理论，进而研究突变控制的技术方法及其在人工心脏控制系统和导航系统中的应用。
人工心脏是彻底解决心肌坏死性疾病的主要途径，但是目前世界上还未研究出能够全部植入人体的有效替代原有心脏功能的人工心脏(简称全植入式人工心脏)。可以说，控制将是全植入式人工心脏的关键技术之一，而人工心脏的控制决不是简单的线性控制或常规的非线性控制。因此，本论文所研究的具有突变机制的控制系统将有助于推动全植入式人工心脏的进展。
突变控制模型就是针对具有突变特征非线性系统而提出的，也可以说是从一个全新的角度对某些非线性控制系统解决方案的一种探索。
将突变理论与控制技术相结合，首次提出了突变控制技术的概念。对于具有突变机制的系统进行了较为深入的研究，并给出了突变控制解决方案，以便实现有效控制。突变在于系统状态的突然改变，状态的改变不只是有快、慢之分，更主要是分析其变化的模式和规律。系统突变有其原因(包括内因和外因)，系统突变的内因是系统运行到一定阶段或状态而自然发生的；系统突变的外因是系统在运行时受到外界的干扰而发生的。系统状态发生突变的现象是存在的，但是以往很少对其突变特性进行研究。当系统中的信息在某一阶段呈现突变状态时，根据其突变特点及归属类型引入不同的势函数模型。将势函数方程引入到控制系统的建模，就可以对系统的变化进行定量描述。本论文就是利用突变理论研究控制系统的突变特性，并提出突变控制模型以描述系统状态变化的规律。突变势函数被引入控制系统，首次提出了突变控制模型；设计了突变预测模型，并将其应用于有关控制系统中。
’
哈尔滨工程人学博士学位论文
人工心脏的控制既属于工程控制论范畴，也属于主物控制论范畴。在对
大量B型超声心动图和ECT图象实验的基础上，建立了人体心脏运动模型，
首次设计了全植入式人工心脏控制系统的突变控制模型。突变控制模型的研
究是将突变理论引入到控制理论中的重要一步，也可以说是两种理论的结合
点，很有可能成为今后研究新的突变控制理论的基础。主于人体心脏运动具
有突变性质，所以为了使人工心脏能够逼近真实心脏的运动过程，那么其控
制系统中就应具有突变控制模型。因此，对于突变控制模型的研究具有较为
重要的理论意义和实际应用价值。
针对舰艇战斗航海需要，将突变控制技术应用到惯性组合导航系统中，
首次设计了导航控制系统应急状态突变控制模型，突变故障诊断模型c
Now many scholars are all at concentrate on the search of the problem of nonlinear control. The nonlinear control of the control system of the law research is one of the lessons that study nowadays in automatic control theory educational circles. This article will be on the foundation work to search a new control theory and the the application of it. That is apply the catastrophe theory to control system , formulating some theories of catastrophe control. The research will put control mechanism in the some and special control occasion. The catastrophe phenomena would be the entry of the problem that will be settled in this article. It will be taken into the analysis and the control of the system, to combine the catastrophe theory with automatic control theory. So we can propose a new concept that is catastrophe control theory. We try the theory to the control system of total artificial heart.
The artificial heart is nowadays more popular in the developed countries such as in the United States, England and so on. They are so concentrated on the availability of artificial heart, it thoroughly clinch the myocardial the critical path of bad dead paroxysm, but the present world is up to now still not bring the prototype that can be all transplanted into the human body to replace function of originally heart(total artificial heart). We can say, and it will be that the key technicality of transplant the artificial heart's lies on control system, but the artificial heart never is the nonlinear control of the simple distribution control or routine. Control system in thesis which is studied about the control system with the catastrophe mechanism will be beneficial to push the holoenzymes to transplant the quinonoid formula artificial the heart's progress.
The model of catastrophe control system is to aim at to the characteristic of nonlinear system and suggested, as well to be from the solution of some nonlinear control systems of an all new angle paraquinones of such kind search.
Combine together the catastrophe theory and control technique, and proposed the technical notion of catastrophe control for the first time. Having done many deep research on the mechanism of catastrophe, giving the solution of the control of catastrophe, to reach the effective control. The catastrophe consists in the much more than only possession of the alteration of the system status alteration, not on the change speed status quick, slow bat batch. The system catastrophe has its own reason (include the inside but also outside). The inside reason happen when system run more naturally, and the outside reason is that outsider interference but occurrence. The phenomena that system status change are very common, but
former few as to it's the catastrophe characteristic steer the research. The article is a take advantages of catastrophe theory research the catastrophe characteristic, and the law of status change of catastrophe control system. Design catastrophe predication form, apply its model into the appliance which is in the in reference to control system under catastrophe the first time.
The control of the artificial heart since is in the category of the engineering control theory, and as well in the category of biological control theory. On the base of having studied with many B mode ultrasound cardiograph}' and ECT image experimenting, create model of human body heart moving, first time design the model total artificial heart of catastrophe control. Research of the model of catastrophe control introduce the catastrophe theory into the control system theory . it is the first step, and as well to could be the combination of the two theory and it will be the basic study of future catastrophe control theory.
Aim at the fleet combat the navigation requirement, will introduce the catastrophe control technique into the integrated navigation system, first time design navigate control system for meeting the need of the navigation of ship, use the model of control under catastrophe theory into integrated navigation. Design the model of catastro
引文
[1] 熊运鸿，高为炳．关于多通道系统的动态递阶镇定．自动化学报．1995(5)：21-25页
[2] 利昂·格拉斯，迈克尔·C·麦基[美]．潘涛等译．从摆钟到混沌——生命的节律．上海远东出版社，1995
[3] 魏宏森，曾国屏．系统论—系统科学哲学．清华大学出版社，1996
[4] 姜璐，王德胜．系统科学新论．华夏出版社，1990
[5] 谷松林．突变理论及应用．甘肃教育出版社，1993
[6] 阿尔诺德[苏]．陈军译．突变理论．商务印书馆，1992
[7] 路肯[德]．凌复华译．协同学：大自然构成的奥秘．上海译文出版社，1995
[8] 方兆本．走出混沌。湖南教育出版社，1995
[9] 赵松年，于允贤．突变理论及其在生物医学中的应用．科学出版社，1987
[10] 桑博德[英]．凌复华译．突变理论入门．上海科学技术文献出版社，1989
[11] 托姆[法]．突变论：思想和应用．上海译文出版社，1998
[12] 何平，赵子都．突变理论及其应用．大连理工大学出版社，1988
[13] 赵子都．一个新的数学分支——突变理论．数学通报．1986(8)：11-15页
[14] 翟连荣，李典漠等．突变论在生态系统分析中的应用．系统工程．1987(3)：21-27页
[15] 程不时．突变理论及其应用．科学通报．1978(9)：25-29页
[16] V. I. Arnold. Catastrophe Theory. Second, Revised and Expanded Edition. Springer-Verlag. 1986
[17] I. Matov. The topological classification of germs of the maximum and minimax functions of a family of functions in general position. USP. Math.Nauk37:1982 (4):129-130P
[18] I. Matov. Ellipticity domains for generic families of homogeneous polynomials and extremum functions. Funkts. Anal. Prilozh. 1985(2):26-36P
[19] P.T. Saunders.An Introduction to Catastrophe Theory. Cambridge university Press. 1980
[20] Zeeman. A Catastrophe model for the stability of ships. In Geometry and Topology. Berlin:Springer. 1976
[21] Gilmore, R., Catastrophe Theory for Science and Engineers, New York, Wiley, 1971
[22] Poston, T., & Stewart, I.N., Catastrophe Theor and its Applications, London: Pitman: 1978
[23] Zeeman, E. C., Catastrophe Theory: Selected Papers1972-1977, Reading Mass: Beniamin. 1997
[24] Thom, R., Sutuctural and Morphogenesis, Reading Mass, Benjamin, 1975
[25] Thom, R., Topological models in biology, Topology, 1969(8): 313-335P
[26] Cobb, L., Stochastic models and multimode distributions, Behav. Sci., 1978(23): 360-374
[27] Lorenz, K.. On Aggression, New York, Rantam, 1967
[28] Ashby, W. R.. Design for A Brain. New York, Barnes & Noble, 1960
[29] Fisher, G. H.. Ambiguity of form: old and new, Perc. Psychophysics, 1968(4), 189-192P
[30] Shafer, M., A catastrophe theory model for ambiguous figure perception, Society Sciences Working Paper, 110a, Univ. of California, Irvine, 1976
[31] Lu.Y.C., Singularity Theory and An Introduction to Catastrophe Theory, Springer, Berlin and New York, 1977
[32] Sussmann, H. J., & Zahler, R. S., Catastrophe theory as applied to the social and biological sciences: A critique, Syntheses, 37, 117-216, 1978
[33] Volkenstein, M. V., Physics and Biology, Academic Press, New York, London, 1982
[34] Bell, G. I., Perelson, A. S., Pimblty, G. H, Jr., Theoretical Immunology Marcal Dekker, Inc., New York and Basel, 1978
[35] 桑德斯，P.T. 著．凌复华译．灾变理论入门．上海科学技术文献出版社，1983
[36] Armstrong, M. A. 著．孙以丰译．李同孚校．基础拓扑学．北京大学出版社，1983
[37] 皮洛，E. C. 著．卢泽愚译．阳含熙，洪加威校．数学生态学引论．科学出版社，1973
[38] 哈肯，H. 著，徐锡申等译，章扬等校，协同学，原子能出版社，1984．
[39] Weinberg, S. L. 著，复旦大学、南开大学、北京大学、山东大学、北京师范大学、厦门大学合译．生物学：对生命本质的探讨．人民教育出版社，1981
[40] 海德，R. M. , 帕特诺德，R. A. 著．刘华、刘静仪、许佐良、蔡添浩译．免疫学，科学出版社，1982
[41] 赵松年、姚国正，儿童多动症(MBD)的数学描述问题．生物化学与生物物理进展．1983(1)：8-12页
[42] Thompson,D' Arcy, On Growth and Form(Abridged edition, Edited by J,T. Bonner) Cambridge University Press, 1966
[43] 寺本英，山口昌哉编．数理通生命，岩波讲座现代生物科学．岩波书店，1975(17)
[44] Braun,M.,Differential Equations and Their Applications, An Introduction to Applied Mathematics,3rd Edition,Springer-Verlag,New York, Heidelberg,Berlin, 1983
[45] 赵松年．突变理论及其在生物学中的应用．大自然探索．1986(1)：2-5页
[46] Dulbecco,R., The Nature of Cancer, Endeanour,New Series,Volume6,1982(2):25-35P
[47] 赵松年，于允贤．预测与决策的动态模型．科学学与科学技术管理．1985(6)：35-47页
[48] Merrill,S.J.,A Geometrical Study of B-Cell Stimulation and Humoral Immune Response,Nonlinear System and Applications,V. Laksmikantham(Ed.),New York,1977
[49] Nicolis,G.,& Prigogine,I.,Self-organiztion in Nonequilibrium System, John Wiley & Sous,1977
[50] 姚国正，赵松年．视觉反差阈值检测的定量模型．生物化学与生物物理进展．1984(5)：13-19页
[51] Goodwin, G.C.and Sin, K.S.,Adaptive Filtering Prediction and Control, Englewood Cliffs, New Jersey,Prentice-Hall, 1984
[52] Box,G.E.P. and Jenkins,G.M.,Time Series Analysis Forecasting and Control, San Francisco,Holden Day,1970
[53] Magad, M. And Sinha, N.K.,Short-term Load Demand Modeling and forecasting: A Review,IEEE Trans.Syst. Man and Cyber.,Vol. SMC-12,No.3,370-382,1982
[54] Connell.P.E.And Clarke, R.T.,Adaptive Hydrological Forecasting-A Review Hydrological Science,Vol.26,No.4,179-205,1981
[55] Hiroyuki Tamura and Tadashi Kondo,Heuristics Free Group Method of Data Handling Algorithm of Generating Optimal Partial Polynomials With Application to Air Pollution Prediction,Int.J.Syst.Sci..,Vol.11,No.9,1095-1111,1980
[56] Pottman, M., Unbehauen,H.and Seborg.D.E.,Application of a General Multi-model Approach for Identification of Highly Nonlinear Process-a Case Study,Int.J.Control,Vol.57,No.1,97-120,1993
[57] Casdagli, M., Nonlinear prediction of Chaos Time Series,Physica D,Vol.35, 335-356,1989
[58] He,X.D.,and Lapedes, A., Nonlinear Prediction by Successive Approximation Using Radial Basis Functions,Physica D,Vol.43,312-318,1991
[59] Wiiner,N.,Extrapolation,Interpolation and Smoothing of Stationary Time Series,John Wiley and Sons,Inc.,New York,1949
[60] Fleck,J.T.,Short Time Prediction of the Motion of a Ship in Waves,Proc.Ist Conf. On Ships and Waves,October 1954,Published by Council on Wave Research and SNAME
[61] Bates, M.R., Book, D.H.,and Powell, F.D., Analog Computer Applications in Predictor Design, IRE Trans.On Elec. Com.,Sep.,Vol. EC-6, No.3, 1957
[62] Kaplan,P.,and Sargent,T.P.,Theoretical Study of the Motions of an Aircraft Carrier at Sea,Oceanics,Inc.Rpt., January,No.65-22,1965
[63] Kaplan,P.,and Ross, D., Comparative Performance of Wave Measuring Systems Mounted on Ships in Motion at Sea,Presented as 4th National Symp. Of Marine Science Inst.,ISA,Coco Beach, Florida, January 1968
[64] Kaplan, P., and Sargent, T.P., A Preliminary Study of Prediction Techniques for Aircraft Carrier Motions at Sea,Oceanics,Inc. Rpt.October 1965, No.65-23
[65] Kaplan,P.,A Study of Prediction Techniques for Aircraft Carrier Motions at Sea, AIAA 6th ASM, No.68-123,1968
[66] Kalman, R.E.,and Brcy, R.S.,New Results in Linear Filtering and Prediction Theory,J. Basic Engr.ASME Trans.,Vol.83D,95-108,1961
[67] Sidar, M., and Doolin, B.F., On the Feasibility of Real Time Prediction of Aircraft Carrier Motion at Sea, NASA Tech. Memo. X-6245,95-1975
[68] Triantafyllou, M., and Bodson, M., Real Time Prediction of Marine Vessel Motion Using Kalman Filtering Techiques,Proc.OTC,Houston,Texas,1982
[69] Triantafyllou, M., Real Time Prediction and Estimation of Ship Motion Using Kalman Filtering Techiques,NASA-CT- 169284,No.82-31637,1982
[70] Triantafyllou, M., Athans, M., Real Time Estimation of Motions of a Destroyer Using Kalman Filtering Techniques, Laboratory for Information and Decision Systems Rep.,MIT Cambridge. MAY, 1983
[71] Triantafyllou, M., Athans, M., Real Time Estimation of the Heaving and Pitching Motions of a Ship Using a Kalman Filter,Proc.Oceanics 81, Boston MA,Sept.1981
[72] Broome D.R.,and Pittaras A.,The Time Prediction of Ship Motions at Sea.OTC 6222,1990
[73] Enochson,The Prediction of Ship Motion at Sea, CTC, 1963
[74] Dazell, J. F., A Nile on Short-time Prediction of Ship Motions J of Ship Research, Vol.9, No.2, 48-52,1965
[75] K.S.Narendar and K. Parthasarathy,Identification and Control of Dynamic System Using Neural Networks.IEEE Trans.on Neural Networks.Vol.1,No.3,pp.4-27,1990
[76] Lin, N. K.,Real Time Estimation of Ship Motion Using ARIMA Filtering Techniques.Proc.ASME OMAE,1987
[77] Davies, W. D. T.,and Noury, R., Aircraft landing Systems on AN/SPN-42 Carrier,Nonlinear and Adaptive Control Technology,New York,1972
[78] Jonnson,W.A Ship Motiontion Prediction Requirement Systems Technology, Inn, Worming Paper,No. 137-6, February,1965
[79] U.Amato, D.T. Vuza, Wavelet Simultaneous Approximation from Samples Affected by Noise,Computers Math.Applic.Vol.36, No.5, pp.101-111,1998
[80] R.Averkamp, C.Houdre, Some Distributional Properties of the Continuous Wavelet Transform of Random Processes,IEEE Trans.Inform.Theory, Vol.44,No.3, pp.1111-1124,1998
[81] David Leporini,Jean-Christophe Pesquet,High-Order Wavelet Packets and Cumulant Field Analysis,IEEE Trans.Inform.Theory,Vol.45,No.3,pp.863-877,1999
[82] Darryl Veitch, Patrice Abry, A Wavelet-Based Joint Estimator of the Parameters of Long-Range Dependence.IEEE Trans.Inform.Theory, Vol.45,No.3,pp.878-897,1999
[83] Beatrice Pesquet-Popescu,Wavelet Packet Decompositions for the Analysis of 2-D Fields with Stationary Fractional Increments,IEEE Trans. Inform.Theory,Vol.45,No.3,pp.1033-1042,1999
[84] Rudolf H. Riedi, Mattew S.Crouse, etc,A Multifractal Wavelet Model with Application to Network Trafic,IEEE Trans.Inform.Theory,Vol.45, No.3, pp.992-1018,1999
[85] Wen Chen,Shuichi Itoh,Junji Shiki,Irregular Sampling Theorems for Wavelet Subspaces,IEEE Trans.Inform.Theory,Vol.44,No.3, pp.1131-1142.1998
[86] Patfice Abry, Darryl Veitch, Wavelet Analysis of Long-Range-Dependent Traffic,IEEE Trans.Inform.Theory,Vol.44, No.1, pp.2-15, 1998
[87] Mark J.Shensa, The Discrete Wavelet Transform:Wedding the A Trous and Mallat Algorithms,IEEE Trans.Signal Processing,Vol.40,No.10, pp.2464-2482,1992
[88] N.Sureshbabu,J.A.Farrell,Wavelet-Based system Identification for Nonlinear Control,IEEE Trans.Automatic Control,Vol.44,No.2,pp.412-417, 1999
[89] Y. Liu, G.G. Walter, A Class of Band-limited Cardinal Wavelets, 数学进展,Vol.26, No.6,pp.523-528,1997
[90] A.V.Spiridonov,I.V. Time.Smoothing Splines for Filtering Strongly Noised Signals, Automation and Remote Control,Vol.59,N0.7,pp.967-972,1998
[91] S.V.Azarov, Myoungho Oh, I.N.Sinitsyn, and V.I.Shin, Method of Normal Approximation in Problems of Adaptive Discrete Filtering and Recogition, Automation and Remote Control,V01.59,No.11,pp. 1517-1525,1998
[92] Kwok-Wo Wong, Andrew Chi-Sing Leung, On-line Successive Synyhesis of Wavelet Networks,Neural Processing Letters 7:91-100,1998
[93] Jun Zhang, Gilbert G. Walter, Yubo Miao, Wan Ngai Wayne Lee, Wavelet Neural Networks for Function Learning, IEEE Trans.Signal Processing, Vol.43, No.6, pp.1485-1496, 1995
[94] B.Delyon,A.Juditsky, A. Benveniste, Accuracy Analysis for Wavelet Approximations,IEEE Trans.On Neural Networks,Vol.6,No.2,pp.332-348,1995
[95] Y.C.Pati, P.S.Krishnaprasad, Analysis and Synthesis of Feedforward Neural Networks Using Discrete Assine Wavelet Transformation.IEEE Trans. Neural Networks,Vol.4,No.1,pp.73-85,1993
[96] Zhang Q. Benveniste A., Wavelet Networks, IEEE Trans. Neural Network,Vol.3, No.6, pp.889-898,1992
[97] D.E.Ovsyanko,Analysis and Optimization of Nonlinear Stochastic Systems that are Asymptoticaly Stable in Ditribution,Automation and Remote Control,Vol.59,No.11,pp.1621-1631,1998
[98] Zhang Q.,Benveniste A. Using Wavelet Networks in Nonpararnetric Estimation, IEEE Trans.Neural Networks,Vol.8, No.2, pp.227-236, 1997
[99] P.O.M.Scokaert,J.B.Rawlings, and E.S.Measows Discrete-time Stability with Perturbations: Application to Model Predictive Control, Automatica,Vol..33, No.3, pp.463-470, 1997
[100] J.H.Lee,Zhenghong Yu,Worst-case Formulations of Model Predictive Control for Systems with Bounded Parameters,Automatica,Vol.33,No.5, pp.763-781,1997
[101] R.K.Mutha, W.R. Cluett, A.Penlidis, Modifying the Prediction Equation for Nonlinear Model-Based Predictive Control,Automatica,Vol.34.No.10,pp.1283-1287,1998
[102] Agostino Bruzzone,Robert Signorile,Simulation and Genetic Algorithms for Ship Planning and Shipyard Layout,Simulation,No.8,pp.74-83,1998
[103] W.H.Livingston,David L.Newman Advances in Implementing Ship Motion Predictiors,AIAA,1980,1.
[104] Ned H.Sandlin, R.S.Ebers,Robert Black,Ship Motion Effects on Landing Impact Loads,AIAA, 1979
[105] Leontaritis, I.J.,Billings,S.A.,Input-Output Parametric Models for Nonlinear Systems, Part Ⅰ: Deterministic Nonlinear Systems,Int.J.Control, Vol.41,No.2,pp.303-328,1985
[106] Leontaritis, I.J., Billings,S.A.,Input-Output Parametric Models for Nonlinear Systems, Part Ⅱ: Stochastic Nonlinear Systems, Int.J.Control,Vol.41,No.2,pp.329-344,1985
[107] P.S.Chang, Alan N. Willson, Analysis of Conjugate Gradient Algorithms for Adaptive Filtering,IEEE Trans.On Signal Processing,Vol.48,No.2, pp.409-418,2000
[108] N.J.Bershad,S.Bouchired,F.Castanie,Stochastic Analysis of Adaptive Gradient Identification of Wiener-Hammerstein Systems for Gaussian Inputs,IEEE Trans.On Signal Processing,Voi.48,No.2,pp.557-560,2000
[109] Pati Y.C, Krishnaprasad P.S, Analysis and Systhesis of Feedforward Neural Networks Using Discrete Affine Wavelet Transformations,IEEE Trans.On Neural Networks,Vol.4, No.1,pp.73-85,1993
[110] Lee S.Y,Gu Y.S.,Szu H. H, Fractional Fourier Transforms,Wavelet Transforms,and Adaptive Neural Networks,Optical Engineering,Vol.33, No.7, pp.2326-2330,1994
[111] Leontaritis,I.J., Billings,S.A.,Input-Output Parametric Models for Nonlinear Systems, Part Ⅱ: Stochastic Nonlinear Systems,Int.J.Control, Vol.41,No.2,1985,pp.329-344
[112] Leontaritis,I.J., Billings, S.A., Input-Output Parametric Models for Nonlinear Systems,Part Ⅰ: Deterministic Nonlinear Systems, Int.J.Control, Vol.41,No.2,1985,pp.303-328
[113] Hwang,J.N.,You, S.S., Lay, S.R., and Jou, I.C., The cascade correlation learning: a projection pursuit learning perspective.IEEE Trans.Neural Networks.Vol.7,No.2,1996,pp.278-289
[114] Ying Zhao and Christopher G.Atkeson,Implementing Projection Pursuit Learning.IEEE Trans.On Neural Networks.Vol.7,No.2,1996, pp.362-272
[115] K.Hornik,Some New Results on Neural Networks Approximation.Neural Networks.Vol.6.1993,pp. 1069-1072
[116] Kruskal,J.B.,Toward a practical method which helps uncover the structure a set of multivariate observation by finding the linear transformation which optimizes a new index of condensation,statistical computation,ed.R.C. Milton and J.A.Nelder,New York, Academic Press 1969
[117] Kruskal,J.B.,Linear transformation of multivariate data to reveal clustering,Multidimensional Scaling:Theory and application in the behavioral Sciences,Vol.Ⅰ,Theory. New York and London,Seminar Press.1972
[118] Switzer,P.,Wright, R. M., Numerical classification applied to certain Jamaican Eocene nummulitids. Mathematical Geology 3,1971,pp.297-311
[119] Switzer, P.,Numerical Classification.Geostatistics, Plenum Press,New York. 1970
[120] Friedman,J.H.,Tukey,J.W.,A Projection pursuit algorithm for exploratory data analysis,IEEE Trans.Computers C-23,1974,pp.881-889.
[121] Friedman,J.H.,Stuetzle,W.,Projection pursuit regression.JASA 76,817-823, 1981
[122] Friedman, J. H. Et al.,Projection pursuit density estimation. JASA 79,599-608, 1984
[123] Fisherkeller,M.A.,Friedman,J.H.,Tikey,J.W.,PRIM-9: An interactive multidimensional data display and analysis system,SLAC-PUB-1408,Standford University.1974
[124] Ying Zhao and Christopher G.Atkeson.Implementing Projection Pursuit Learning.IEEE Trans. On Neural Networks [J].Vol.7.,No.2, pp.362-272,1996
[125] 蒋知俭，实用医学实验设计，北京医科大学、中国协和医科大学联合出版社，1992年4月
[126] 蒋知俭，医学统计学概念、方法及应用，黑龙江科学技术出版社，1987年
[127] 蔡锁章，计算方法，北京工业学院出版社，1987年12月
[128] 李岳生，齐东旭，样条函数方法，科学出版社，1979年6月
[129] 苏步青，刘鼎元，计算几何，上海科学出版社，1982年6月
[130] 李介谷等，图像处理技术，上海交通大学出版社，1988年6月
[131] 李士勇等，模糊控制和智能控制理论与应用，哈尔滨工业大学出版社，1992年12月
[132] 荆仁杰等，计算机图像处理，浙江大学出版社，1990年6月
[133] 徐建华，图像处理与分析，科学出版社，1992年1月
[134] 孙尧，现代成像技术原理，黑龙江科学技术出版社，1993年6月
[135] 陈延标，数字图像处理，人民邮电出版社，1990年5月
[136] 陶祖莱，生物流体力学，科学出版社，1984年9月
[137] Andrew Seit,G. Care, Finite Element Modelling of Cardiac Mechanics,IEEE Region 10 Conference on Computer and Communication System, Sept.1990,pp. 496-475
[138] JS Suri, RM Haralick ,FH Sheeham, Accurate Left Ventricle Apex Position and Boundary Estimation from Noisy Ventriculograms,IEEE Computer in Cardiology 1996, pp.257-260
[139] Mitsuji Muneyasu, Yuji Wada,Takao Hinamoto Edge-Preserving Smoothing by Adaptive Nonlinear Filters Based on Fussy Control Laws,IEEE1996, pp.785-788.
[140] Steve M.,et al.Computer-Assisted Edge Detection in Two-Dimensional Echocardiography:Comparison with Automatic Data,American J.of Cardiology,1984, Vol.53,pp.1380-1387
[141] 周晓东，钱蕴秋等，二维超声心动图定量检测局部左室收缩功能的计算方法，中华物理医学杂志，1991年第13卷第一期，PP.19-24
[142] 钱蕴秋等，冠心病患者超声心动图、心电图与冠脉造影对照研究，中华心血管病杂志，1991年，pp.19-34
[143] 刘金耀等，左室局部收缩功能在冠心病诊断中的应用价值，心功能杂志，1995年9月，第7卷第3期，pp.137-140
[144] 周晓东等，两维超声心动图定量检测不同程度心肌缺血时局部左心收缩功能的变化，中国超声医学杂志，1994年1月，第3卷第1期，pp.41-44
[145] 张军等，超声心动图对急性心肌梗塞检测和定量诊断的实验研究，中国超声医学杂志，1985年，第5卷第2期，pp.90
[146] R.Bajcsy et al,Evaluation of registration of PET images with CT images,Tech. Rep. Dept.of Computer Information,Sci.,Univ.of Pennsylvania,1988
[147] K.R.Smith, K. Joarder,and R.D.Bucholta,Multimodality image analysis and display methods for improved tumor localization in stereotactic neurosurgery,Proc.Annu.IEEE Conference,vol.13 no.1,1991,pp.210
[148] 刘兴党等，图像融合及其临床应用，国外医学·放射医学核医学分册，1996年第20卷第4期，pp．156-158
[149] A.C.Evans,S.Marrett,et al,MR-PET correlation in three-dimensions using a volume-of-interest(VOI) atlas,J.Cerebral Blood Flow Metabolism,1991,vol.11,no.1,pp.A69-A78
[150] C.A.Pelizzari et al, Accurate three-dimensional registration of CT, PET and/or MR images of the brain,J.Computer Assisted Tomography,1989,vol.13,no.1,pp.20-26
[151] A.V.Levy et al, The metabolic centroid method for PET brain image analysis,J. Cerebral Blood Flow Metabolism,1989, vol.9,pp.388-397
[152] Steven M.J.,Jeremy Graham, and Shaun Voigt, An application of image matching/fusion in medcine,IEEE,1996, pp42-47
[153] Jingxi Zhang,Michel F. Levesque et al, Multimodality Imageing of Brain Structures for Stereotactic Surgery,Radiology,1990;175;pp435-441
[2] 利昂·格拉斯，迈克尔·C·麦基[美]．潘涛等译．从摆钟到混沌——生命的节律．上海远东出版社，1995
[3] 魏宏森，曾国屏．系统论—系统科学哲学．清华大学出版社，1996
[4] 姜璐，王德胜．系统科学新论．华夏出版社，1990
[5] 谷松林．突变理论及应用．甘肃教育出版社，1993
[6] 阿尔诺德[苏]．陈军译．突变理论．商务印书馆，1992
[7] 路肯[德]．凌复华译．协同学：大自然构成的奥秘．上海译文出版社，1995
[8] 方兆本．走出混沌。湖南教育出版社，1995
[9] 赵松年，于允贤．突变理论及其在生物医学中的应用．科学出版社，1987
[10] 桑博德[英]．凌复华译．突变理论入门．上海科学技术文献出版社，1989
[11] 托姆[法]．突变论：思想和应用．上海译文出版社，1998
[12] 何平，赵子都．突变理论及其应用．大连理工大学出版社，1988
[13] 赵子都．一个新的数学分支——突变理论．数学通报．1986(8)：11-15页
[14] 翟连荣，李典漠等．突变论在生态系统分析中的应用．系统工程．1987(3)：21-27页
[15] 程不时．突变理论及其应用．科学通报．1978(9)：25-29页
[16] V. I. Arnold. Catastrophe Theory. Second, Revised and Expanded Edition. Springer-Verlag. 1986
[17] I. Matov. The topological classification of germs of the maximum and minimax functions of a family of functions in general position. USP. Math.Nauk37:1982 (4):129-130P
[18] I. Matov. Ellipticity domains for generic families of homogeneous polynomials and extremum functions. Funkts. Anal. Prilozh. 1985(2):26-36P
[19] P.T. Saunders.An Introduction to Catastrophe Theory. Cambridge university Press. 1980
[20] Zeeman. A Catastrophe model for the stability of ships. In Geometry and Topology. Berlin:Springer. 1976
[21] Gilmore, R., Catastrophe Theory for Science and Engineers, New York, Wiley, 1971
[22] Poston, T., & Stewart, I.N., Catastrophe Theor and its Applications, London: Pitman: 1978
[23] Zeeman, E. C., Catastrophe Theory: Selected Papers1972-1977, Reading Mass: Beniamin. 1997
[24] Thom, R., Sutuctural and Morphogenesis, Reading Mass, Benjamin, 1975
[25] Thom, R., Topological models in biology, Topology, 1969(8): 313-335P
[26] Cobb, L., Stochastic models and multimode distributions, Behav. Sci., 1978(23): 360-374
[27] Lorenz, K.. On Aggression, New York, Rantam, 1967
[28] Ashby, W. R.. Design for A Brain. New York, Barnes & Noble, 1960
[29] Fisher, G. H.. Ambiguity of form: old and new, Perc. Psychophysics, 1968(4), 189-192P
[30] Shafer, M., A catastrophe theory model for ambiguous figure perception, Society Sciences Working Paper, 110a, Univ. of California, Irvine, 1976
[31] Lu.Y.C., Singularity Theory and An Introduction to Catastrophe Theory, Springer, Berlin and New York, 1977
[32] Sussmann, H. J., & Zahler, R. S., Catastrophe theory as applied to the social and biological sciences: A critique, Syntheses, 37, 117-216, 1978
[33] Volkenstein, M. V., Physics and Biology, Academic Press, New York, London, 1982
[34] Bell, G. I., Perelson, A. S., Pimblty, G. H, Jr., Theoretical Immunology Marcal Dekker, Inc., New York and Basel, 1978
[35] 桑德斯，P.T. 著．凌复华译．灾变理论入门．上海科学技术文献出版社，1983
[36] Armstrong, M. A. 著．孙以丰译．李同孚校．基础拓扑学．北京大学出版社，1983
[37] 皮洛，E. C. 著．卢泽愚译．阳含熙，洪加威校．数学生态学引论．科学出版社，1973
[38] 哈肯，H. 著，徐锡申等译，章扬等校，协同学，原子能出版社，1984．
[39] Weinberg, S. L. 著，复旦大学、南开大学、北京大学、山东大学、北京师范大学、厦门大学合译．生物学：对生命本质的探讨．人民教育出版社，1981
[40] 海德，R. M. , 帕特诺德，R. A. 著．刘华、刘静仪、许佐良、蔡添浩译．免疫学，科学出版社，1982
[41] 赵松年、姚国正，儿童多动症(MBD)的数学描述问题．生物化学与生物物理进展．1983(1)：8-12页
[42] Thompson,D' Arcy, On Growth and Form(Abridged edition, Edited by J,T. Bonner) Cambridge University Press, 1966
[43] 寺本英，山口昌哉编．数理通生命，岩波讲座现代生物科学．岩波书店，1975(17)
[44] Braun,M.,Differential Equations and Their Applications, An Introduction to Applied Mathematics,3rd Edition,Springer-Verlag,New York, Heidelberg,Berlin, 1983
[45] 赵松年．突变理论及其在生物学中的应用．大自然探索．1986(1)：2-5页
[46] Dulbecco,R., The Nature of Cancer, Endeanour,New Series,Volume6,1982(2):25-35P
[47] 赵松年，于允贤．预测与决策的动态模型．科学学与科学技术管理．1985(6)：35-47页
[48] Merrill,S.J.,A Geometrical Study of B-Cell Stimulation and Humoral Immune Response,Nonlinear System and Applications,V. Laksmikantham(Ed.),New York,1977
[49] Nicolis,G.,& Prigogine,I.,Self-organiztion in Nonequilibrium System, John Wiley & Sous,1977
[50] 姚国正，赵松年．视觉反差阈值检测的定量模型．生物化学与生物物理进展．1984(5)：13-19页
[51] Goodwin, G.C.and Sin, K.S.,Adaptive Filtering Prediction and Control, Englewood Cliffs, New Jersey,Prentice-Hall, 1984
[52] Box,G.E.P. and Jenkins,G.M.,Time Series Analysis Forecasting and Control, San Francisco,Holden Day,1970
[53] Magad, M. And Sinha, N.K.,Short-term Load Demand Modeling and forecasting: A Review,IEEE Trans.Syst. Man and Cyber.,Vol. SMC-12,No.3,370-382,1982
[54] Connell.P.E.And Clarke, R.T.,Adaptive Hydrological Forecasting-A Review Hydrological Science,Vol.26,No.4,179-205,1981
[55] Hiroyuki Tamura and Tadashi Kondo,Heuristics Free Group Method of Data Handling Algorithm of Generating Optimal Partial Polynomials With Application to Air Pollution Prediction,Int.J.Syst.Sci..,Vol.11,No.9,1095-1111,1980
[56] Pottman, M., Unbehauen,H.and Seborg.D.E.,Application of a General Multi-model Approach for Identification of Highly Nonlinear Process-a Case Study,Int.J.Control,Vol.57,No.1,97-120,1993
[57] Casdagli, M., Nonlinear prediction of Chaos Time Series,Physica D,Vol.35, 335-356,1989
[58] He,X.D.,and Lapedes, A., Nonlinear Prediction by Successive Approximation Using Radial Basis Functions,Physica D,Vol.43,312-318,1991
[59] Wiiner,N.,Extrapolation,Interpolation and Smoothing of Stationary Time Series,John Wiley and Sons,Inc.,New York,1949
[60] Fleck,J.T.,Short Time Prediction of the Motion of a Ship in Waves,Proc.Ist Conf. On Ships and Waves,October 1954,Published by Council on Wave Research and SNAME
[61] Bates, M.R., Book, D.H.,and Powell, F.D., Analog Computer Applications in Predictor Design, IRE Trans.On Elec. Com.,Sep.,Vol. EC-6, No.3, 1957
[62] Kaplan,P.,and Sargent,T.P.,Theoretical Study of the Motions of an Aircraft Carrier at Sea,Oceanics,Inc.Rpt., January,No.65-22,1965
[63] Kaplan,P.,and Ross, D., Comparative Performance of Wave Measuring Systems Mounted on Ships in Motion at Sea,Presented as 4th National Symp. Of Marine Science Inst.,ISA,Coco Beach, Florida, January 1968
[64] Kaplan, P., and Sargent, T.P., A Preliminary Study of Prediction Techniques for Aircraft Carrier Motions at Sea,Oceanics,Inc. Rpt.October 1965, No.65-23
[65] Kaplan,P.,A Study of Prediction Techniques for Aircraft Carrier Motions at Sea, AIAA 6th ASM, No.68-123,1968
[66] Kalman, R.E.,and Brcy, R.S.,New Results in Linear Filtering and Prediction Theory,J. Basic Engr.ASME Trans.,Vol.83D,95-108,1961
[67] Sidar, M., and Doolin, B.F., On the Feasibility of Real Time Prediction of Aircraft Carrier Motion at Sea, NASA Tech. Memo. X-6245,95-1975
[68] Triantafyllou, M., and Bodson, M., Real Time Prediction of Marine Vessel Motion Using Kalman Filtering Techiques,Proc.OTC,Houston,Texas,1982
[69] Triantafyllou, M., Real Time Prediction and Estimation of Ship Motion Using Kalman Filtering Techiques,NASA-CT- 169284,No.82-31637,1982
[70] Triantafyllou, M., Athans, M., Real Time Estimation of Motions of a Destroyer Using Kalman Filtering Techniques, Laboratory for Information and Decision Systems Rep.,MIT Cambridge. MAY, 1983
[71] Triantafyllou, M., Athans, M., Real Time Estimation of the Heaving and Pitching Motions of a Ship Using a Kalman Filter,Proc.Oceanics 81, Boston MA,Sept.1981
[72] Broome D.R.,and Pittaras A.,The Time Prediction of Ship Motions at Sea.OTC 6222,1990
[73] Enochson,The Prediction of Ship Motion at Sea, CTC, 1963
[74] Dazell, J. F., A Nile on Short-time Prediction of Ship Motions J of Ship Research, Vol.9, No.2, 48-52,1965
[75] K.S.Narendar and K. Parthasarathy,Identification and Control of Dynamic System Using Neural Networks.IEEE Trans.on Neural Networks.Vol.1,No.3,pp.4-27,1990
[76] Lin, N. K.,Real Time Estimation of Ship Motion Using ARIMA Filtering Techniques.Proc.ASME OMAE,1987
[77] Davies, W. D. T.,and Noury, R., Aircraft landing Systems on AN/SPN-42 Carrier,Nonlinear and Adaptive Control Technology,New York,1972
[78] Jonnson,W.A Ship Motiontion Prediction Requirement Systems Technology, Inn, Worming Paper,No. 137-6, February,1965
[79] U.Amato, D.T. Vuza, Wavelet Simultaneous Approximation from Samples Affected by Noise,Computers Math.Applic.Vol.36, No.5, pp.101-111,1998
[80] R.Averkamp, C.Houdre, Some Distributional Properties of the Continuous Wavelet Transform of Random Processes,IEEE Trans.Inform.Theory, Vol.44,No.3, pp.1111-1124,1998
[81] David Leporini,Jean-Christophe Pesquet,High-Order Wavelet Packets and Cumulant Field Analysis,IEEE Trans.Inform.Theory,Vol.45,No.3,pp.863-877,1999
[82] Darryl Veitch, Patrice Abry, A Wavelet-Based Joint Estimator of the Parameters of Long-Range Dependence.IEEE Trans.Inform.Theory, Vol.45,No.3,pp.878-897,1999
[83] Beatrice Pesquet-Popescu,Wavelet Packet Decompositions for the Analysis of 2-D Fields with Stationary Fractional Increments,IEEE Trans. Inform.Theory,Vol.45,No.3,pp.1033-1042,1999
[84] Rudolf H. Riedi, Mattew S.Crouse, etc,A Multifractal Wavelet Model with Application to Network Trafic,IEEE Trans.Inform.Theory,Vol.45, No.3, pp.992-1018,1999
[85] Wen Chen,Shuichi Itoh,Junji Shiki,Irregular Sampling Theorems for Wavelet Subspaces,IEEE Trans.Inform.Theory,Vol.44,No.3, pp.1131-1142.1998
[86] Patfice Abry, Darryl Veitch, Wavelet Analysis of Long-Range-Dependent Traffic,IEEE Trans.Inform.Theory,Vol.44, No.1, pp.2-15, 1998
[87] Mark J.Shensa, The Discrete Wavelet Transform:Wedding the A Trous and Mallat Algorithms,IEEE Trans.Signal Processing,Vol.40,No.10, pp.2464-2482,1992
[88] N.Sureshbabu,J.A.Farrell,Wavelet-Based system Identification for Nonlinear Control,IEEE Trans.Automatic Control,Vol.44,No.2,pp.412-417, 1999
[89] Y. Liu, G.G. Walter, A Class of Band-limited Cardinal Wavelets, 数学进展,Vol.26, No.6,pp.523-528,1997
[90] A.V.Spiridonov,I.V. Time.Smoothing Splines for Filtering Strongly Noised Signals, Automation and Remote Control,Vol.59,N0.7,pp.967-972,1998
[91] S.V.Azarov, Myoungho Oh, I.N.Sinitsyn, and V.I.Shin, Method of Normal Approximation in Problems of Adaptive Discrete Filtering and Recogition, Automation and Remote Control,V01.59,No.11,pp. 1517-1525,1998
[92] Kwok-Wo Wong, Andrew Chi-Sing Leung, On-line Successive Synyhesis of Wavelet Networks,Neural Processing Letters 7:91-100,1998
[93] Jun Zhang, Gilbert G. Walter, Yubo Miao, Wan Ngai Wayne Lee, Wavelet Neural Networks for Function Learning, IEEE Trans.Signal Processing, Vol.43, No.6, pp.1485-1496, 1995
[94] B.Delyon,A.Juditsky, A. Benveniste, Accuracy Analysis for Wavelet Approximations,IEEE Trans.On Neural Networks,Vol.6,No.2,pp.332-348,1995
[95] Y.C.Pati, P.S.Krishnaprasad, Analysis and Synthesis of Feedforward Neural Networks Using Discrete Assine Wavelet Transformation.IEEE Trans. Neural Networks,Vol.4,No.1,pp.73-85,1993
[96] Zhang Q. Benveniste A., Wavelet Networks, IEEE Trans. Neural Network,Vol.3, No.6, pp.889-898,1992
[97] D.E.Ovsyanko,Analysis and Optimization of Nonlinear Stochastic Systems that are Asymptoticaly Stable in Ditribution,Automation and Remote Control,Vol.59,No.11,pp.1621-1631,1998
[98] Zhang Q.,Benveniste A. Using Wavelet Networks in Nonpararnetric Estimation, IEEE Trans.Neural Networks,Vol.8, No.2, pp.227-236, 1997
[99] P.O.M.Scokaert,J.B.Rawlings, and E.S.Measows Discrete-time Stability with Perturbations: Application to Model Predictive Control, Automatica,Vol..33, No.3, pp.463-470, 1997
[100] J.H.Lee,Zhenghong Yu,Worst-case Formulations of Model Predictive Control for Systems with Bounded Parameters,Automatica,Vol.33,No.5, pp.763-781,1997
[101] R.K.Mutha, W.R. Cluett, A.Penlidis, Modifying the Prediction Equation for Nonlinear Model-Based Predictive Control,Automatica,Vol.34.No.10,pp.1283-1287,1998
[102] Agostino Bruzzone,Robert Signorile,Simulation and Genetic Algorithms for Ship Planning and Shipyard Layout,Simulation,No.8,pp.74-83,1998
[103] W.H.Livingston,David L.Newman Advances in Implementing Ship Motion Predictiors,AIAA,1980,1.
[104] Ned H.Sandlin, R.S.Ebers,Robert Black,Ship Motion Effects on Landing Impact Loads,AIAA, 1979
[105] Leontaritis, I.J.,Billings,S.A.,Input-Output Parametric Models for Nonlinear Systems, Part Ⅰ: Deterministic Nonlinear Systems,Int.J.Control, Vol.41,No.2,pp.303-328,1985
[106] Leontaritis, I.J., Billings,S.A.,Input-Output Parametric Models for Nonlinear Systems, Part Ⅱ: Stochastic Nonlinear Systems, Int.J.Control,Vol.41,No.2,pp.329-344,1985
[107] P.S.Chang, Alan N. Willson, Analysis of Conjugate Gradient Algorithms for Adaptive Filtering,IEEE Trans.On Signal Processing,Vol.48,No.2, pp.409-418,2000
[108] N.J.Bershad,S.Bouchired,F.Castanie,Stochastic Analysis of Adaptive Gradient Identification of Wiener-Hammerstein Systems for Gaussian Inputs,IEEE Trans.On Signal Processing,Voi.48,No.2,pp.557-560,2000
[109] Pati Y.C, Krishnaprasad P.S, Analysis and Systhesis of Feedforward Neural Networks Using Discrete Affine Wavelet Transformations,IEEE Trans.On Neural Networks,Vol.4, No.1,pp.73-85,1993
[110] Lee S.Y,Gu Y.S.,Szu H. H, Fractional Fourier Transforms,Wavelet Transforms,and Adaptive Neural Networks,Optical Engineering,Vol.33, No.7, pp.2326-2330,1994
[111] Leontaritis,I.J., Billings,S.A.,Input-Output Parametric Models for Nonlinear Systems, Part Ⅱ: Stochastic Nonlinear Systems,Int.J.Control, Vol.41,No.2,1985,pp.329-344
[112] Leontaritis,I.J., Billings, S.A., Input-Output Parametric Models for Nonlinear Systems,Part Ⅰ: Deterministic Nonlinear Systems, Int.J.Control, Vol.41,No.2,1985,pp.303-328
[113] Hwang,J.N.,You, S.S., Lay, S.R., and Jou, I.C., The cascade correlation learning: a projection pursuit learning perspective.IEEE Trans.Neural Networks.Vol.7,No.2,1996,pp.278-289
[114] Ying Zhao and Christopher G.Atkeson,Implementing Projection Pursuit Learning.IEEE Trans.On Neural Networks.Vol.7,No.2,1996, pp.362-272
[115] K.Hornik,Some New Results on Neural Networks Approximation.Neural Networks.Vol.6.1993,pp. 1069-1072
[116] Kruskal,J.B.,Toward a practical method which helps uncover the structure a set of multivariate observation by finding the linear transformation which optimizes a new index of condensation,statistical computation,ed.R.C. Milton and J.A.Nelder,New York, Academic Press 1969
[117] Kruskal,J.B.,Linear transformation of multivariate data to reveal clustering,Multidimensional Scaling:Theory and application in the behavioral Sciences,Vol.Ⅰ,Theory. New York and London,Seminar Press.1972
[118] Switzer,P.,Wright, R. M., Numerical classification applied to certain Jamaican Eocene nummulitids. Mathematical Geology 3,1971,pp.297-311
[119] Switzer, P.,Numerical Classification.Geostatistics, Plenum Press,New York. 1970
[120] Friedman,J.H.,Tukey,J.W.,A Projection pursuit algorithm for exploratory data analysis,IEEE Trans.Computers C-23,1974,pp.881-889.
[121] Friedman,J.H.,Stuetzle,W.,Projection pursuit regression.JASA 76,817-823, 1981
[122] Friedman, J. H. Et al.,Projection pursuit density estimation. JASA 79,599-608, 1984
[123] Fisherkeller,M.A.,Friedman,J.H.,Tikey,J.W.,PRIM-9: An interactive multidimensional data display and analysis system,SLAC-PUB-1408,Standford University.1974
[124] Ying Zhao and Christopher G.Atkeson.Implementing Projection Pursuit Learning.IEEE Trans. On Neural Networks [J].Vol.7.,No.2, pp.362-272,1996
[125] 蒋知俭，实用医学实验设计，北京医科大学、中国协和医科大学联合出版社，1992年4月
[126] 蒋知俭，医学统计学概念、方法及应用，黑龙江科学技术出版社，1987年
[127] 蔡锁章，计算方法，北京工业学院出版社，1987年12月
[128] 李岳生，齐东旭，样条函数方法，科学出版社，1979年6月
[129] 苏步青，刘鼎元，计算几何，上海科学出版社，1982年6月
[130] 李介谷等，图像处理技术，上海交通大学出版社，1988年6月
[131] 李士勇等，模糊控制和智能控制理论与应用，哈尔滨工业大学出版社，1992年12月
[132] 荆仁杰等，计算机图像处理，浙江大学出版社，1990年6月
[133] 徐建华，图像处理与分析，科学出版社，1992年1月
[134] 孙尧，现代成像技术原理，黑龙江科学技术出版社，1993年6月
[135] 陈延标，数字图像处理，人民邮电出版社，1990年5月
[136] 陶祖莱，生物流体力学，科学出版社，1984年9月
[137] Andrew Seit,G. Care, Finite Element Modelling of Cardiac Mechanics,IEEE Region 10 Conference on Computer and Communication System, Sept.1990,pp. 496-475
[138] JS Suri, RM Haralick ,FH Sheeham, Accurate Left Ventricle Apex Position and Boundary Estimation from Noisy Ventriculograms,IEEE Computer in Cardiology 1996, pp.257-260
[139] Mitsuji Muneyasu, Yuji Wada,Takao Hinamoto Edge-Preserving Smoothing by Adaptive Nonlinear Filters Based on Fussy Control Laws,IEEE1996, pp.785-788.
[140] Steve M.,et al.Computer-Assisted Edge Detection in Two-Dimensional Echocardiography:Comparison with Automatic Data,American J.of Cardiology,1984, Vol.53,pp.1380-1387
[141] 周晓东，钱蕴秋等，二维超声心动图定量检测局部左室收缩功能的计算方法，中华物理医学杂志，1991年第13卷第一期，PP.19-24
[142] 钱蕴秋等，冠心病患者超声心动图、心电图与冠脉造影对照研究，中华心血管病杂志，1991年，pp.19-34
[143] 刘金耀等，左室局部收缩功能在冠心病诊断中的应用价值，心功能杂志，1995年9月，第7卷第3期，pp.137-140
[144] 周晓东等，两维超声心动图定量检测不同程度心肌缺血时局部左心收缩功能的变化，中国超声医学杂志，1994年1月，第3卷第1期，pp.41-44
[145] 张军等，超声心动图对急性心肌梗塞检测和定量诊断的实验研究，中国超声医学杂志，1985年，第5卷第2期，pp.90
[146] R.Bajcsy et al,Evaluation of registration of PET images with CT images,Tech. Rep. Dept.of Computer Information,Sci.,Univ.of Pennsylvania,1988
[147] K.R.Smith, K. Joarder,and R.D.Bucholta,Multimodality image analysis and display methods for improved tumor localization in stereotactic neurosurgery,Proc.Annu.IEEE Conference,vol.13 no.1,1991,pp.210
[148] 刘兴党等，图像融合及其临床应用，国外医学·放射医学核医学分册，1996年第20卷第4期，pp．156-158
[149] A.C.Evans,S.Marrett,et al,MR-PET correlation in three-dimensions using a volume-of-interest(VOI) atlas,J.Cerebral Blood Flow Metabolism,1991,vol.11,no.1,pp.A69-A78
[150] C.A.Pelizzari et al, Accurate three-dimensional registration of CT, PET and/or MR images of the brain,J.Computer Assisted Tomography,1989,vol.13,no.1,pp.20-26
[151] A.V.Levy et al, The metabolic centroid method for PET brain image analysis,J. Cerebral Blood Flow Metabolism,1989, vol.9,pp.388-397
[152] Steven M.J.,Jeremy Graham, and Shaun Voigt, An application of image matching/fusion in medcine,IEEE,1996, pp42-47
[153] Jingxi Zhang,Michel F. Levesque et al, Multimodality Imageing of Brain Structures for Stereotactic Surgery,Radiology,1990;175;pp435-441