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Marr边缘检测算法的研究，,提出了不等间隔采样和非均匀量化相结合的数字化方法-Marr edge detection algorithm research, interval ranging from the non-uniform sampling and quantization combination of digital methods
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实现对数压缩PCM和线性PCM的信噪比特性曲线的仿真，非均匀量化级数为n=8和n=6。-realization of a number of PCM compressed and linear PCM signal-to-noise ratio of the characteristic curve simulation, non-uniform quantization Series n = 8 and n = 6.
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模拟信号转换成数字形式,必须要经过量化才能实现。标量量化的方法包括均匀量化和非均匀量化两种,这两种方法都会带来精度的损失。文中探讨了模拟信源量化的最优算法,并用C语言实现了高斯信源在不同量化电平下均匀量化和非均匀量化的最优步长的数值计算。通过对计算结果进行比较,给出了非均匀量化优于均匀量化的具体结论。-Analog signals into digital form, you must go through quantification can be achieved. Scalar unifo
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uniform quantization in matlab
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Companding is essentially a technique for achieving non-uniform quantization. There are basically 2 methods which are most popular in literature.:-A-law companding and u-law companding. These algorithms help in achieving to an extend, compression. Th
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μ律PCM编码，小信号放大，大信号缩小，非均匀量化实现的一种方式，实用。-μ-law PCM coding, small signal amplification, large signal narrow, one way to achieve a non-uniform quantization, and practical.
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均匀量化,利用matlab建立均匀量化的模型,及绘制量化误差曲线-Uniform quantization
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uniform quantization for visual c++.
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进行均匀量化误差分析，并且有仿真图，分别是输入信号和量化信号对比，采样样值和8级均匀量化后的样值，均匀量化信噪比随编码位数的变化(Error analysis of uniform quantization)
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