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英文最新版数字图像处理基础，包括信号与系统，信号表达与量化，快速算法与结构，数字滤波，统计信号处理，自适应滤波，信号重建，时频和多率信号处理。-Emphasizing theoretical concepts, Digital Signal Processing Fundamentals provides comprehensive coverage of the basic foundations of DSP and includes the following parts: Signals
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This matlab code read bmp file and seperate it to R,G,B components. And also quantize the image.
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SVD小波域自适应量化盲水印算法SVD wavelet domain watermarking algorithm for adaptive quantization-SVD wavelet domain watermarking algorithm for adaptive quantization
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简要介绍了标量量化和矢量量化的相关知识。标量量化包括了固定量化、自适应量化、基于视觉的量化等。矢量量化包括了其基本原理和LBG,Lattice两种实现方法。-Brief scalar quantization and vector quantization related knowledge. Scalar quantization including fixed quantization, adaptive quantization, the quantization based on the
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Matlab神经网络工具箱函数涉及的网络模型有，感知机网络、线性神经网络、BP神经网络、径向基神经网络、自组织神经网络、学习向量量化神经网络、Elman神经网络、Hopfield神经网络、自适应滤波和控制系统网络等。-Matlab neural network toolbox function involving network model have a perceptron and linear neural network, BP neural network, RBF neural net
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竞争型神经网络 主要有自主型竞争、自组特征映射、自适应共振理论、学习向量量化等神经网络-Competitive neural networks are mainly autonomous competition, since the group feature mapping, adaptive resonance theory, learning vector quantization neural network
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