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The inhabited environments are MIMO, uncertainly, and nonlinear complex systems. This paper presents a novel intelligent fuzzy agent(IFA) based on input-output associational algorithm for intelligent inhabited environments. An input-output dynamic associational algorithm based on Hebb learning is proposed, which can divide a complex system into multiple simple systems and eliminate the irrelevant...
In the paper, support vector machine is presented to detection for vehicle' s overlap, which has stronger generalization ability than the algorithm based on the empirical risk, such as artificial neural network. In the process of detection for vehicle's overlap, principal component analysis is used to extract the features and reduce the dimension of features. Then, detection model for vehicle's overlap...
This paper addresses the questions of improving convergence performance for back propagation (BP) neural network. For traditional BP neural network algorithm, the learning rate selection is depended on experience and trial. In this paper, based on Taylor formula the function relationship between the total quadratic training error change and connection weights and biases changes is obtained, and combined...
The permanent magnet synchronous motor (PMSM) is a dynamic, multi-variable and non-linear system, and the conventional PID control method is very difficult to meet the requirement for high accuracy control. This paper presents an approach of control for PMSM servo system using fuzzy radius basis function (f-RBF) neural network which has the advantages of strong adaptive ability and nonlinear approximation...
The conventional analytic hierarchy process (AHP) has the drawback of its invariable weights system (IWS) and the composite ranking approaches based on IWS, incapable of reflecting intrinsic characteristics of complex evaluation issues, such as nonlinearity, emergence, etc. To overcome the above drawback, with the idea of weight varying adopted, an improved ranking approach to AHP alternatives based...
An adaptive approach to the estimation of the instantaneous frequency (IF) of non-stationary and nonlinear multi-component signals is presented. This method relates to the newly developed empirical mode decomposition (EMD) and Teager Kaiser energy operator (TKEO). EMD can adaptively decompose signal into a series of zero mean amplitude modulation-frequency modulation (AM-FM) intrinsic mode functions...
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