Fundamental study on neural chips that processes high-frequency carrier signals adaptively and nonlinearly

神经网络在用于高频应用（超高速信号处理）时必须实现为模拟硬件（非脉冲型），或者实现为大规模并行接口（超高并行处理）。然而，由于模拟神经网络经常受到噪声的影响（包括权值精度不足和大的漂移），其不稳定行为尚未得到广泛的研究。高频区的定时不稳定性、失真和噪声频谱的特征和来源仍然不清楚。我们的目标是通过阐明这种弱点的起源，实现一个有效有用的模拟硬件。我们对两种联想记忆（递归网络）的特性进行了测量;例如，分立元件网络和VDEC定制芯片网络。测量结果表明，回忆过程在很大程度上受到神经元回路和突触电阻对称性的影响。因此，我们设计了两个新的电路元件：（1）高信号电压对称的突触电阻和（2）高延迟时间相等的神经元。我们已经制作了一个新的网络芯片，将它们通过VDEC和测量的特性。我们已经证明，我们的芯片有一个突出的召回性能和对称性和延迟调谐平等有这样的循环决策电路的关键影响。新的电路元件通常适用于包括未来超快涡轮解码器的循环判决芯片。

Neural networks have to be implemented as an analog hardware (non-pulse type) when used for high-frequency applications (ultra high speed signal processing) or as a massively parellel interface (ultra highly parallel processing). Nevertheless, the analog neural networks have not been investigated widely because oft the unstable behavior affected by noise (including insufficient accuracy of weights and large drift). The characteristics and origins of timing instability, distortion and noise spectrum in high frequency regions has still been unclear. We aim at realizing an effectively useful analog hardware by elucidating the origin of such weakness. We conducted measurement of characteristics of two kinds of associative memories (recurrent networks) ; i. e., a discrete component network and a VDEC custom chip network. The measurement results showed that the recalling process is affected to a great extent by the symmetry of the neuron-unit circuit and the synaptic resistors. Therefore, we have designed two new circuit elements (1)highty signal-voltage-symmetric synaptic resistors and (2)highly delay-time-equal neuron. We have fabricated a new network chip incorporating them through the VDEC and measured the characteristics. We have demonstrated that our chip has an outstanding recalling performance and the symmetry and the delay-tune equality has a critical influence on such recurrent decision circuit. The new circuit elements are applicable to recurrent decision chips in general including future ultra-fast turbo decoders.