Description: In this project we analyze and design the minimum mean-square error (MMSE) multiuser receiver for uniformly quantized synchronous code division multiple access (CDMA) signals in additive white Gaussian noise (AWGN) channels.This project is mainly based on the representation of uniform quantizer by gain plus additive noise model. Based on this model, we derive the weight vector and the output signal-to-interference ratio (SIR) of the MMSE receiver. The effects of quantization on the MMSE receiver performance is characterized in a single parameter named 鈥漞quivalent noise variance鈥? The optimal quantizer stepsize which maximizes the MMSE receiver output SNR is also determined.-In this project we analyze and design the minimum mean-square error (MMSE) multiuser receiver for uniformly quantized synchronous code division multiple access (CDMA) signals in additive white Gaussian noise (AWGN) channels.This project is mainly based on the representation of uniform quantizer by gain plus additive noise model. Based on this model, we derive the weight vector and the output signal-to-interference ratio (SIR) of the MMSE receiver. The effects of quantization on the MMSE receiver performance is characterized in a single parameter named 鈥漞quivalent noise variance鈥? The optimal quantizer stepsize which maximizes the MMSE receiver output SNR is also determined. Platform: |
Size: 147456 |
Author:prasad |
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Description: L3_1.m: 純量量化器的設計(程式)
L3_2.m: 量化造成的假輪廓(程式)
L3_3.m: 向量量化器之碼簿的產生(程式)
L3_4.m: 利用LBG訓練三個不同大小與維度的碼簿並分別進行VQ(程式)
gau.m: ML量化器設計中分母的計算式(函式)
gau1.m: ML量化器設計中分子的計算式(函式)
LBG.m: LBG訓練法(函式)
quantize.m:高斯機率密度函數的非均勻量化(函式)
VQ.m: 向量量化(函式)
L3_2.bmp: 影像檔
lena.mat: Matlab的矩陣變數檔
-L3_1.m: scalar quantizer design (the program) L3_2.m: quantitative result of the false contour (the program) L3_3.m: Vector quantizer code book of the generation (the program) L3_4.m: training in the use of LBG three different size and dimension of the code book and separate VQ (program) gau.m: ML quantizer design in the denominator of the calculation formula (function) gau1.m: ML quantizer design in the calculation of molecule-type ( function) LBG.m: LBG training method (function) quantize.m: Gaussian probability density function of the non-uniform quantization (function) VQ.m: vector quantization (function) L3_2.bmp: image file lena.mat: Matlab matrix variable file Platform: |
Size: 191488 |
Author:Oki |
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Description: 理解使用向量量化进行图像量化的原理:对序列中的许多样本进行联合量化,用一个值代替相似的一组值,减少量化误差;
掌握向量量化器码书设计的方法,此次实验使用LBG算法设计码书;
3. 对LBG算法的理解和使用;
4.Matlab矩阵数据的处理。-Understood that the use of vector quantization for image quantized principle: a number of samples of the sequence are jointly quantified, instead of a similar set of values with a value, to reduce the quantization error master Vector quantizer codebook design, the experimental use LBG algorithm codebook design 3. LBG algorithm to understand and use 4.Matlab matrix data processing. Platform: |
Size: 16384 |
Author:黎鸿朗 |
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