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[matlabSTDM

Description: 利用STDM方法嵌入水印信息,可设置量化步长,选择各种经典的攻击方式,控制攻击强弱,返回误码率和峰值信噪比-Stdm method using embedded watermark information, to set the quantization step size, choose a variety of classic attacks, controlling the strength of the attack and returned to the bit error rate and peak signal to noise ratio
Platform: | Size: 56320 | Author: 张湛 | Hits:

[matlabU_PCM

Description: 格式 [sqnr,a_quan,code]=u_pcm(a,n) 输入样值序列a 、量化电平数目n, 程序计算量化间隔、进行均匀量化、进行编码、计算量化信噪比, 返回量化信噪比squn、编码前的量化序列a_quan、编码后的码序列code。 -Format [sqnr, a_quan, code] = u_pcm (a, n) input sample value sequence a, the number of quantization levels n, the calculation procedures to quantify interval, the uniform quantization, coding, computing quantization noise ratio, return quantization noise ratio squn, to quantify the pre-coding sequence a_quan, coding sequences after the code.
Platform: | Size: 1024 | Author: wx | Hits:

[Communication-Mobilewirelesscomm

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 | Hits:

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