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数字信号处理一种基于matlab 文件内容/conv(卷积部分)dupconv重叠保留法freqcirconv频域圆周卷积freqconv频域卷积timecirconv时域圆周卷积timeconv时域域卷积积/fft(频域分析部分)d2fft基2FFTdft DFT最简化程序源码dtftDTFT演示/fir(fir滤波器设计)fir 的到fir滤波器hngetwindow 的到fir滤波器窗函数wn
-Digital signal processing matlab file content
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本文主要讲讲怎样对Mat矩阵进行mask操作，其实也就是对Mat矩阵的滤波操作，俗称卷积，参考文献为opencv自带的tutiol及其code.
开发环境：ubuntu12.04+opencv2.4.2+Qt4.8.2+QtCreator2.5.
实验功能：
单击Open image按钮，手动选择所需滤波的原图片。
单击Setting按钮，弹出对话框，选择滤波所用的模式，这里有2种模式，分别为自己实现滤波功能和采用opencv自带的滤波函数filter2D实现。
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C. S. BURRUS and T. W. PARKS: DFT/FFT AND CONVOLUTION
ALGORITHMS: THEORY AND IMPLEMENTATION
JOHN R. TREICHLER, C. RICHARD JOHNSON, JR., and MICHAEL G.
LARIMORE: THEORY AND DESIGN OF ADAPTIVE FILTERS
T. W. PARKS and C. S. BURRUS: DIGITAL FILTE
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DSP课程设计大量源代码
1.模拟采样定理的实现
2.模拟滤波器的设计
3.切比雪夫I型低通滤波器设计
4.凯塞窗设计数字高通滤波器
5.数字FIR滤波器的设计方法
6.线性卷积和循环卷积的设计
-The DSP course design a large number of source code
1. Realization of analog sampling theorem
2 the design of analog filters
3 cut
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代码给出了数字图像处理图像复原运算方法中的自适应滤波、正则化滤波、盲去卷积滤波等滤波方法的实现过程，经matlab调试运行成功，效果明显-Code gives a computing method of digital image processing image restoration, adaptive filtering, regularization filter, blind go convolution filtering and other filtering methods to
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IIR滤波器实现及FT的时域卷积定理验证-IIR filter realization and FT of time domain convolution theorem verification
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DSP算法程序，包含FFT、FIR、IIR、卷积、自适应滤波器等算法-DSP algorithm contains the FFT, FIR, IIR, convolution, adaptive filter algorithm
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design of:
1.butterworth bandpass filter
2.butterworth bandstop filter
3.butterworth lowpass filter
4.butterworth highpass filter
for the given specifications using matlab
design of:
1.hilbert transformer
2.differentiator
using
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使用DSP28335 FIR（finite impulse response） 滤波器算法试验 对位相乘求和法实现卷积-DSP FIR (finite impulse response) filter algorithm test， on bit multiply convolution summation method to achieve
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codes for linear convolution and fir filter in C and scilab
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在matlab环境下，自编的高斯滤波函数，其中的二维卷积运算也是自编的，没有使用matlab自带conv2函数。-In the matlab environment, self-Gaussian filter function, which is a two-dimensional convolution self, without using matlab built conv2 function.
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低通和高通分别作卷积的方法。用巴特沃斯滤波器构造数字二分频器。-Low-pass and high-pass respectively, for convolution approach. Digital Butterworth filter structure with two dividers.
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3GPP空间信道模型 (扩展)，该程序产生信道滤波器抽头，离散信号与其卷积，即表明信号通过该信道。-SCM 3GPP Spatial Channel Mode(extended).
The program produce channel filter taps. Then,discrete signal do convolution operation with taps, which indicates that signal is through this channel.
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FFT-based FIR Filter is a unit to perform the finite impulse responce filter based on the Fast Fourier Transform (FFT). It performs the convolution of the unlimited signal sequence with the synthesized impulse responce of the length of Ni=N/2 samples
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Gabor滤波器的原理是 其脉冲响应为一个谐波函数（即下式中的余弦函数）和一个高斯函数的乘积。根据信号与系统理论，时频域的卷积和乘积互为傅里叶变换。Gabor滤波器的傅里叶变换为谐波和高斯函数各自傅里叶变换的卷积-The principle of the Gabor filter is a harmonic of its impulse response function (i.e., the cosine function in the formula) and the product of
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压缩文件中给出了已知系统传递函数及输入信号的情况下，求解系统输出响应的四种方法，即差分方程法，卷积法，DFT法以及滤波器设计方法；此外还包含创建窗及其频率响应的matlab设计。-Known compressed file system transfer function is given and the case of the input signal, the output response of the system to solve the four methods, namely th
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计算并显示滤波器的ambiguity function，分析滤波器的时间频域特性，使用卷积矩阵运算速度快-Calculates and displays the filter ambiguity function, time-frequency domain analysis filter characteristics, the use of fast convolution matrix operations
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Gabor滤波 默认5个尺度，8个方向 每次卷积后将结果拉成一维向量，再将每次卷积结果串起来。
-Gabor filter default 5 scale, eight directions of each convolution result will be pulled into one-dimensional vector, and then each convolution results to string together.
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This function calculates a room s impulse response for an arbitrarily positioned sound source in a rbitrarily dimensioned rectangular room, as it would be heard at an arbitrary position. The output of RIR.m is a vector and can be used as an FIR filte
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This function plots a Gaussian impulse response, unit impulse and the
convolution/deconvolution of both using MATLAB s filter . Specifically
it uses filter rather than deconv to do the deconvolution and thereby
returns the original Gaussian
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