In recent years, machine-learning techniques, particularly deep learning, have outperformed
traditional time-series forecasting approaches in many contexts, including univariate and …

回声状态网络是近年来新兴的一种递归神经网络, 独特而简单的训练方式以及高精度的训练结果
已使其成为当前研究的热点之一. 在该网络中, 引入了储备池计算模式这一新的神经网络的建设 …

An increased number of bio-inspired face recognition systems have emerged in recent
decades owing to their intelligent problem-solving ability, flexibility, scalability, and adaptive …

The electrical signals triggering the heart's contraction are governed by non-linear
processes that can produce complex irregular activity, especially during or preceding the …

As one of the most important paradigms of recurrent neural networks, the echo state network
(ESN) has been applied to a wide range of fields, from robotics to medicine, finance, and …

The development of conceptual models using causal loop diagrams and their variants is a
key step in the system dynamics modeling process. This work seeks to explore to what …

Echo state network (ESN) has gained wide acceptance in the field of time series prediction,
relying on sufficiently complex reservoir connections to remember the historical features of …

In this paper, the echo state network (ESN) memory capacity, which represents the amount
of input data an ESN can store, is analyzed for a new type of deep ESNs. In particular, two …

Echo State Networks (ESNs), a form of recurrent neural network developed in the field of
Reservoir Computing, show significant potential for use as a tool in the design of mappings …

Based on small-world network theory, we have developed a brain-inspired photonic
reservoir computing (RC) network system utilizing quantum dot spin-vertical-cavity surface …