一个有效的模拟环境,用于细胞神经网络和模拟阵列

K. R. Krieg, L. Chua
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引用次数: 1

摘要

只提供摘要形式。传统的基于电路的细胞神经网络和模拟阵列的仿真非常缓慢和繁琐。如果程序的数据和计算结构能够反映模拟阵列的体系结构,那么所涉及的大部分计算和内存空间都可以减少。作者介绍了这样一个模拟器的细节,命名为ASIM。ASIM执行的计算直接来自描述每个节点处理的非线性微分方程,内部数据表示反映了模拟阵列的结构。ASIM是模拟具有规则结构的连续时间连续变量计算阵列的图形环境,其连通性是最近邻的,其节点处理可以用一组非线性微分方程来描述。用户只需要指定节点处理方程和与相邻处理器的连接。输入和输出是图形化的,并显示数组中所有变量的状态作为时间的函数。用户可以结合任何内部变量的迭代来找到最优的处理策略或邻域组织。为了帮助评估将在VLSI中制造的算法,用户可以指定任何计算变量的方差来模拟制造公差的影响,并且可以指定某些变量具有相关的噪声分量。这两个特征使ASIM成为开发模拟阵列和细胞神经网络算法的理想助手,这些算法对实现变异性更具鲁棒性。ASIM程序运行在基于80386的IBM PC/AT计算机上,使用MS-DOS操作系统。它需要2mb的扩展内存和一个VGA兼容的显卡。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
ASIM, an efficient simulation environment for cellular neural networks and analog arrays
Summary form only given. Traditional circuit-based simulation of cellular neural networks and analog arrays is very slow and cumbersome. Much of the computation and memory space involved could be reduced if the data and computational structures of the program could mirror the architecture of the analog array. The authors present the details of such a simulator, named ASIM. The computations performed by ASIM are derived directly from the nonlinear differential equations describing the processing at each node and the internal data representation mirrors the architecture of analog arrays. ASIM is a graphical environment for simulating continuous-time continuous-variable computational arrays which have a regular structure, whose connectivity is nearest-neighbor, and whose nodal processing can be described by a set of nonlinear differential equations. The user need specify only the equations for nodal processing and the connectivity to neighboring processors. Input and output are graphical and show the state of all variables in the array as a function of time. The user may incorporate iteration of any internal variable to find optimal processing strategies or neighborhood organization. To aid the evaluation of algorithms which are to be fabricated in VLSI, the use can specify variances in any computational variable to simulate the effect of fabrication tolerances and may specify that certain variables have associated noise components. Both of these features make ASIM an ideal aid in developing analog array and cellular neural network algorithms which are more robust to implementation variability. The ASIM program runs on 80386 based IBM PC/AT computers using the MS-DOS operating system. It requires 2 Mbytes of extended memory and a VGA compatible graphics card.<>
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