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Adaptation

  • The adaptive Neural Network Library is a collection of blocks that implement several Adaptive Neural

    The adaptive Neural Network Library is a collection of blocks that implement several Adaptive Neural Networks featuring different Adaptation algorithms.~..~ There are 11 blocks that implement basically these 5 kinds of neural networks: 1) Adaptive Linear Network (ADALINE) 2) Multilayer Layer Perceptron with Extended Backpropagation algorithm (EBPA) 3) Radial Basis Functions (RBF) Networks 4) RBF Networks with Extended Minimal Resource Allocating algorithm (EMRAN) 5) RBF and Piecewise Linear Networks with Dynamic Cell Structure (DCS) algorithm A simulink example regarding the approximation of a scalar nonlinear function of 4 variables is included

    標簽: Neural collection implement Adaptive

    上傳時間: 2013-12-23

    上傳用戶:teddysha

  • 基于Volterra濾波器混沌時間序列多步預測 作者:陸振波

    基于Volterra濾波器混沌時間序列多步預測 作者:陸振波,海軍工程大學 歡迎同行來信交流與合作,更多文章與程序下載請訪問我的個人主頁 電子郵件:luzhenbo@sina.com 個人主頁:luzhenbo.88uu.com.cn 參考文獻: 1、張家樹.混沌時間序列的Volterra自適應預測.物理學報.2000.03 2、Scott C.Douglas, Teresa H.-Y. Meng, Normalized Data Nonlinearities for LMS Adaptation. IEEE Trans.Sign.Proc. Vol.42 1994 文件說明: 1、original_MultiStepPred_main.m 程序主文件,直接運行此文件即可 2、original_train.m 訓練函數 3、original_test.m 測試函數 4、LorenzData.dll 產生Lorenz離散序列 5、normalize_1.m 歸一化 6、PhaSpaRecon.m 相空間重構 7、PhaSpa2VoltCoef.dll 構造 Volterra 自適應 FIR 濾波器的輸入信號矢量 Un 8、TrainTestSample_2.m 將特征矩陣前 train_num 個為訓練樣本,其余為測試樣本 9、FIR_NLMS.dll NLMS自適應算法

    標簽: Volterra 濾波器 混沌 時間序列

    上傳時間: 2013-12-16

    上傳用戶:talenthn

  • penMesh is a generic and efficient data structure for representing and manipulating polygonal meshes

    penMesh is a generic and efficient data structure for representing and manipulating polygonal meshes. OpenMesh is developed at the Computer Graphics Group, RWTH Aachen , as part of the OpenSGPlus project, is funded by the German Ministry for Research and Education ( BMBF), and will serve as geometry kernel upon which the so-called high level primitives (e.g. subdivision surfaces or progressive meshes) of OpenSGPlus are built. It was designed with the following goals in mind : Flexibility : provide a basis for many different algorithms without the need for Adaptation. Efficiency : maximize time efficiency while keeping memory usage as low as possible. Ease of use : wrap complex internal structure in an easy-to-use interface.

    標簽: manipulating representing and efficient

    上傳時間: 2015-10-14

    上傳用戶:米卡

  • The adaptive Neural Network Library is a collection of blocks that implement several Adaptive Neural

    The adaptive Neural Network Library is a collection of blocks that implement several Adaptive Neural Networks featuring different Adaptation algorithms.

    標簽: Neural collection implement Adaptive

    上傳時間: 2015-12-01

    上傳用戶:181992417

  • Semantic analysis of multimedia content is an on going research area that has gained a lot of atten

    Semantic analysis of multimedia content is an on going research area that has gained a lot of attention over the last few years. Additionally, machine learning techniques are widely used for multimedia analysis with great success. This work presents a combined approach to semantic Adaptation of neural network classifiers in multimedia framework. It is based on a fuzzy reasoning engine which is able to evaluate the outputs and the confidence levels of the neural network classifier, using a knowledge base. Improved image segmentation results are obtained, which are used for Adaptation of the network classifier, further increasing its ability to provide accurate classification of the specific content.

    標簽: multimedia Semantic analysis research

    上傳時間: 2016-11-24

    上傳用戶:蟲蟲蟲蟲蟲蟲

  • 很經典的一個算法。大家做工程和通信用的著。遺傳算法(Genetic Algorithm)是模擬達爾文的遺傳選擇和自然淘汰的生物進化過程的計算模型

    很經典的一個算法。大家做工程和通信用的著。遺傳算法(Genetic Algorithm)是模擬達爾文的遺傳選擇和自然淘汰的生物進化過程的計算模型,是一種通過模擬自然進化過程搜索最優解的方法,它是有美國Michigan大學J.Holland教授于1975年首先提出來的,并出版了頗有影響的專著《Adaptation in Natural and Artificial Systems》,GA這個名稱才逐漸為人所知,J.Holland教授所提出的GA通常為簡單遺傳算法(SGA)。

    標簽: Algorithm Genetic 算法

    上傳時間: 2017-02-09

    上傳用戶:wkchong

  • Abstract—Stable direct and indirect decentralized adaptive radial basis neural network controllers

    Abstract—Stable direct and indirect decentralized adaptive radial basis neural network controllers are presented for a class of interconnected nonlinear systems. The feedback and Adaptation mechanisms for each subsystem depend only upon local measurements to provide asymptotic tracking of a reference trajectory. Due to the functional approximation capabilities of radial basis neural networks, the dynamics for each subsystem are not required to be linear in a set of unknown coeffi cients as is typically required in decentralized adaptive schemes. In addition, each subsystem is able to adaptively compensate for disturbances and interconnections with unknown bounds.

    標簽: decentralized controllers Abstract adaptive

    上傳時間: 2017-08-17

    上傳用戶:gdgzhym

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