Ultra parallel computation using wave interference as means of weighted sum : Holographic neural computing

该项目开发了一种使用相干波的干涉作为人工神经网络的加权SNM计算的直接手段的超并行计算的新方法。相干波（如声波和激光）可以相互干涉，合成波的振幅由它们的相位差决定。这种现象可以被用作加权和计算的手段。加权和是人工神经网络中神经元的一种基本运算，在人工智能领域得到了广泛的研究。所开发的系统仅使用波发射和接收设备作为其组件。这些分量的相对位置决定了波的相位差，从而决定了加权求和的方式。这种计算被编码为这些组件在二维表面上的位置。以这种方式，该系统既不需要通信线，也不需要诸如加法器和乘法器之类的计算设备。在这个项目的两年中，我们提出了几种实现这一想法的方法，并在嘈杂和扭曲的波浪条件下研究了所提出的系统的计算能力。

he project developed a novel approach for ultra parallel computation using interference of coherent waves as direct means of weighted snm computation for artificial neural networks. Coherent waves such as acoustic waves and lasers can interfere with each other and the amplitude of synthesized wave is determined by their phase differences. This phenomena can be utilized as means of weighted sum computation. Weighted sum is a basic operation of a neuron in the artificial neural networks which have been extensively studied for artificial intelligence purposes. The developed system uses only wave emitting and receiving devices as its components. The relative positions of these components determines the phase differences of the waves and, consequently, the ways of weighted sum. The kind of computation is coded as the positions of these components arranged on a two dimensional surface. In this fashion, the system does not require neither communication wires nor computation devices such as adder and multiplier. During the two years of this project, we proposed several ways of implementing this idea and examined the computational capabilities of the proposed systems under noisy and distorted wave conditions.