Random-Pulse Machines

A new kind of machine is proposed, in which the continuous variable is represented as a probability of a pulse occurrence at a certain sampling time. It is shown that threshold gates can be used as simple and inexpensive processors such as adders and multipliers. In fact, for a random-pulse sequence, any Boolean operation among individual pulses will correspond to an algebraic expression among the variables represented by their respective average pulse-rates. So, any logical gate or network performs an algebraic operation. Considering the possible simplicity of these random-pulse processors, large systems can be built to perform parallel analog computation on large amounts of input data. The conventional analog computer has a topological simulation structure that can be readily carried over to the processing of functions of time and of one, two, or perhaps even three space variables. Facility of gating, inherent to any form of pulse-coding, allows the construction of stored-connection parallel analog computers made to process functions of time and two space variables. This paper considers this technique of random-pulse computation and its potential implications. Problems of realization, application examples, and alternate coding schemes are discussed. Speed, accuracy, and uncertainty dispersion are estimated. A brief comparison is made between random-pulse processors and biological neutrons.

[1]  Harold K. Skramstad,et al.  A combined analog-digital differential analyzer , 1959, IRE-AIEE-ACM '59 (Eastern).

[2]  Shuji Doshita,et al.  The Automatic Speech Recognition System for Conversational Sound , 1963, IEEE Trans. Electron. Comput..

[3]  Yngvar Lundh Digital techniques for small computations , 1959 .

[4]  W. Siebert Processing neuroelectric data , 1959 .

[5]  Karl Steinbuch,et al.  Adaptive Systems in Pattern Recognition , 1963, IEEE Trans. Electron. Comput..

[6]  Sergio Telles Ribeiro Comments on Pulsed-Data Hybrid Computers , 1964, IEEE Trans. Electron. Comput..

[7]  Bruce H. McCormick,et al.  The Illinois Pattern Recognition Computer-ILLIAC III , 1963, IEEE Trans. Electron. Comput..

[8]  Hermann Schmid An Operational Hybrid Computing System Provides Analog-Type Computation with Digital Elements , 1963, IEEE Trans. Electron. Comput..

[9]  J. Gregory,et al.  The SOLOMON Computer , 1963, IEEE Trans. Electron. Comput..

[10]  Haruhisa Ishida,et al.  A Learning Network Using Adaptive Threshold Elements , 1965, IEEE Trans. Electron. Comput..

[11]  Paul E. Wood Digital Differential Analyzers with Arbitrary Stored Interconnections , 1965, IEEE Trans. Electron. Comput..

[12]  Willem A. Bergeijk,et al.  Analog models of neural mechanism , 1962, IRE Trans. Inf. Theory.

[13]  Rodolfo Gonzalez A Multilayer Iterative Circuit Computer , 1963, IEEE Trans. Electron. Comput..

[14]  W. Pitts,et al.  What the Frog's Eye Tells the Frog's Brain , 1959, Proceedings of the IRE.

[15]  H. D. Block The perceptron: a model for brain functioning. I , 1962 .

[16]  Erik V. Bohn A Pulse Position Modulation Analog Computer , 1960, IRE Trans. Electron. Comput..

[17]  J. K. Hawkins,et al.  Eulogismographic Nonlinear Optical Image Processing for Pattern Recognition , 1964 .