Method of detecting echo state network weak signal in chaotic background and based on improved teaching-learning-based optimization(ITLBO) algorithm

Abstract

The invention discloses a method for detecting the weak signal of the echo state network based on the improved teaching optimization algorithm in the chaotic background. The method adopts the improved teaching optimization algorithm (ITLBO) algorithm to optimize the parameters of the echo state network model. Determine the number of optimized parameters, the value of the reserve pool size N and the sparsity SD, and encode the rest of the parameters; secondly, find the optimal echo state network model parameter combination through the teaching stage, learning stage, and feedback stage of ITLBO and compare these Modeling, training and prediction of parameters, analysis of the single-step prediction error and judging whether there is a weak target signal in the chaotic background noise, using this method to simulate the Lorenz chaotic background and the actual sea clutter signal, accurately and quickly Detect weak signals; overcome the shortcomings of difficulty in selecting parameters of the echo state network model, and improve work efficiency.

Description

technical field [0001] A detection method, especially a method for detecting weak signals in an echo state network. Background technique [0002] Chaos phenomenon is a kind of irregular motion produced by nonlinear deterministic system, which widely exists in many fields such as meteorology, hydrology, communication and economy. Chaos has the characteristics of internal randomness, overall stability and local instability, short-term predictability and long-term unpredictability. In recent years, with the continuous deepening of chaos theory research and its wide application in signal processing, automatic control, power and financial short-term forecasting and other fields, the modeling and forecasting of chaotic time series has become a very important research in the field of chaos. direction. [0003] With the emergence of artificial intelligence methods, more and more researchers apply them to time series forecasting. Among many artificial intelligence methods, neural ...

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Problems solved by technology

[0004] In order to solve the deficiencies in the prior art, the object of the present invention is to provide a method for detecting the weak signal of the echo state network based on the improved teaching optimization algorithm in a chaotic background, and the method utilizes the improved optimization teaching algorithm (ITLBO) to optimize the echo state network model Parameter method, so as to detect the weak signal in the chaotic background, overcome the shortcomings of difficult selection of echo state network model parameters, and improve work efficiency

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