基于脉冲神经膜系统的有符号并行乘法器设计
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摘要
针对现有的脉冲神经膜系统只能进行无符号二进制整数的乘法运算,而实际应用中更多地需要处理有符号整数的乘法运算,故用脉冲神经膜系统实现有符号整数的乘法运算更能满足实际需要。首先,设计了并行乘法器中并行数据的数值位与符号位的分离。其次,设计了用来计算任意两个有符号整数乘法的并行乘法器的脉冲神经膜系统。接着,设计了并行乘法器中两个并行数据的数值位与符号位的分离。最后,设计了能够执行任意两个有符号整数乘法运算的脉冲神经膜系统。系统仿真表明,所设计的脉冲神经膜系统都能准确地执行有符号整数的乘法运算。当前问题的解决,将有助于脉冲神经膜系统的生物型CPU的设计。
For the existing spiking neural membrane system,it can only multiply unsigned binary integers,but in practice,it is more necessary to multiply signed integers. Therefore,it is more suitable to multiply signed integers by spiking neural membrane system. Firstly,the separation of numeric bit and symbol bit of parallel data in parallel multiplier is designed. Secondly,a spiking neural membrane system is designed to compute the parallel multiplier of any two signed integer multiplications. Then,the separation of numeric bit and symbol bit of two parallel data in parallel multiplier is designed. Finally,a spiking neural membrane system capable of performing any two signed integer multiplications is designed. The simulation results show that the system can perform the multiplication of signed integers accurately. The solution of the current problem will contribute to the design of biological CPU for spiking neural membrane system.
For the existing spiking neural membrane system,it can only multiply unsigned binary integers,but in practice,it is more necessary to multiply signed integers. Therefore,it is more suitable to multiply signed integers by spiking neural membrane system. Firstly,the separation of numeric bit and symbol bit of parallel data in parallel multiplier is designed. Secondly,a spiking neural membrane system is designed to compute the parallel multiplier of any two signed integer multiplications. Then,the separation of numeric bit and symbol bit of two parallel data in parallel multiplier is designed. Finally,a spiking neural membrane system capable of performing any two signed integer multiplications is designed. The simulation results show that the system can perform the multiplication of signed integers accurately. The solution of the current problem will contribute to the design of biological CPU for spiking neural membrane system.
引文
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[2]Zhang X Y,Zeng X X,Pan L Q.A spiking neural P system for performing multiplication of two arbitrary natural numbers[J].Chinese Journal of Computer,2009,32(12):2362-2372.
[3]Song T,Pan L,Paunt G.Asynchronous spiking neural P systems with local synchronization[J].Inf.Sci,2013,219(1):197-207.
[4]Song B,Pan L,M.J.Pérez-Jiménez.Tissue Psystems with protein on cells[J].Fundam Inform,2016,144(1):77-107.
[5]Wu Tingfang,Zhang zhiqing,Paun Gheorghe.Cell-like spiking neural P systems[J].Theor Comput Sci,2016(623):180-189.
[6]Pan L,Wang J,H.J.Hoogeboom.Asynchronous extended spiking neural P systems with astrocytes[C].International Conference on Membrane Computing,berlin heidelberg:soringer-verlag,2012:243-256.
[7]Zhang X,Zhang X,Song T,et al.Spiking neural P systems with thresholds[J].Neural Comput,2017,26(7):1340-1361.
[8]Zhang G,Rang H,Neri F,et al.An optimization spiking neural P system for approximately solving combinatorial optimization problems[J].Int.J.Neural Syst,2014,24(5):1-16.
[9]Pan LQ,Zeng X,Zhang X,Time-free spiking neural P systems[J].NeuralComput,2011,23(5):1320-1342.
[10]A.Ramanujan,K.Krithivasan.Control words of transition P systems[J].Advances in Intelligent Systems andComputing,2013(201):145-155.
[11]S.Verlan,J.Quiros,Fast hardware implementation of P systems[C].International Conference on Membrane Computing,berlin hidelberg:soringer-verlag,2013:404-423.
[12]Pan LQ,M.J.P'erez-Jim'enez.Spiking neural Psystems with neuron division and budding[J].Science China Information Sciences,2011,54(8):1596-1607.