Description: 信号与系统基础知识包括连续信号与模型、离散信号与模型；常用信号变换包括Z变换、Chirp Z变换、FFT变换、DCT变换和Hilbert变换等；离散系统结构包括IIR、FIR和Lattice结构；IIR滤波器设计包括模拟和数字低通、高通、带通与带阻滤波器设计，以及基于冲激响应不变法和双线性Z变换法的IlR滤波器设计等；FIR滤波器设计包括基于窗函数、频率抽样法和切比雪大逼近法的FIR滤波器设计；平稳信号分析包括经典功率谱估计、基于参数模型的功率谱估计和基于非参数模型的功率谱估计；非平稳信号分析包括STFT变换、Gabor展开、Wigner-Ville分布与Choi-Williams分布；非高斯信号分析包括基于非参数法的双谱估计、基于参数模型的双谱估计，以及双谱估计的应用；信号处理的GUI实现包括滤波器设计与分析的FDATool工具和滤波器设计与信号分析的SPTool工具。-signals and systems based on knowledge, including continuous signal with the model, discrete signal and model; Common signals include transform Z transform, chirp Z-transform, FFT transform. DCT and Hilbert transform; Discrete system architecture including IIR, FIR and Lattice structure; IIR filter design, including analog and digital low-pass, high-pass, band-pass and band stop filter design, Based on the impulse response of the same law and bilinear Z transform the IlR filter design; FIR filter design including on the basis of the window function, frequency sampling and snow all over the big approximation of FIR filter design; stationary signal analysis include classical power spectrum estimation, Based on the model parameters of the power spectrum estimation and non - parametric model b Platform: |
Size: 101182 |
Author:james |
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Description: 信号与系统基础知识包括连续信号与模型、离散信号与模型；常用信号变换包括Z变换、Chirp Z变换、FFT变换、DCT变换和Hilbert变换等；离散系统结构包括IIR、FIR和Lattice结构；IIR滤波器设计包括模拟和数字低通、高通、带通与带阻滤波器设计，以及基于冲激响应不变法和双线性Z变换法的IlR滤波器设计等；FIR滤波器设计包括基于窗函数、频率抽样法和切比雪大逼近法的FIR滤波器设计；平稳信号分析包括经典功率谱估计、基于参数模型的功率谱估计和基于非参数模型的功率谱估计；非平稳信号分析包括STFT变换、Gabor展开、Wigner-Ville分布与Choi-Williams分布；非高斯信号分析包括基于非参数法的双谱估计、基于参数模型的双谱估计，以及双谱估计的应用；信号处理的GUI实现包括滤波器设计与分析的FDATool工具和滤波器设计与信号分析的SPTool工具。-signals and systems based on knowledge, including continuous signal with the model, discrete signal and model; Common signals include transform Z transform, chirp Z-transform, FFT transform. DCT and Hilbert transform; Discrete system architecture including IIR, FIR and Lattice structure; IIR filter design, including analog and digital low-pass, high-pass, band-pass and band stop filter design, Based on the impulse response of the same law and bilinear Z transform the IlR filter design; FIR filter design including on the basis of the window function, frequency sampling and snow all over the big approximation of FIR filter design; stationary signal analysis include classical power spectrum estimation, Based on the model parameters of the power spectrum estimation and non- parametric model b Platform: |
Size: 101376 |
Author:james |
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Description: 离散余弦变换，然后主成分分析进行数据降维，用于模式识别，如人脸识别，掌纹，表情，指纹等识别。-Discrete cosine transform, and then principal component analysis for data dimensionality reduction for pattern recognition, such as face recognition, palmprint, face, fingerprint and other identification. Platform: |
Size: 16384 |
Author:陈浩 |
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Description: 该代码仅计算了一个101×101尺寸的Gabor函数变换，得到均值和方差。代码采用两种卷积计算方式，从结果中可以看出，快速傅立叶变换卷积的效率是离散二维叠加和卷积的近50倍。
-The code is only the calculation of a 101 × 101 size Gabor function transformation, the mean and variance. Convolutional code using two methods of calculation can be seen from the results, fast Fourier transform convolution efficiency are two-dimensional discrete convolution superposition and nearly 50 times. Platform: |
Size: 3072 |
Author:康俊芳 |
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Description: Feature extraction is a key issue in contentbased
image retrieval (CBIR). In the past, a number of
texture features have been proposed in literature,
including statistic methods and spectral methods.
However, most of them are not able to accurately capture
the edge information which is the most important texture
feature in an image. Recent researches on multi-scale
analysis, especially the curvelet research, provide good
opportunity to extract more accurate texture feature for
image retrieval. Curvelet was originally proposed for
image denoising and has shown promising performance.
In this paper, a new image feature based on curvelet
transform has been proposed. We apply discrete curvelet
transform on texture images and compute the low order
statistics from the transformed images. Images are then
represented using the extracted texture features. Retrieval
results show, it significantly outperforms the widely used
Gabor texture feature. Platform: |
Size: 1426432 |
Author:Swati |
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Description: 离散信号Gabor展开的理论及实现颇为繁琐。其中包括离散Gabor变换的标架理论、周期序列的离散Gabor变换、非周期序列的离散Gabor变换以及各种快速算法等。此程序给出给出了一个线性调频信号的Gabor变换。-Gabor expansion of discrete signals and the realization of the theory is quite cumbersome. Including discrete Gabor transform frame theory, the periodic sequence of discrete Gabor transform, non-periodic sequence of discrete Gabor transform and a variety of fast algorithms. This procedure gives a linear FM signal is given the Gabor transform. Platform: |
Size: 1024 |
Author:yangan |
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Description: this paper gives a brief discription of different methodology for face detection and facial expresssion recognition.for face detection Exhaustive search,Branch and Bound,Viola-Jones methods can be used. for expression recognition gabor filter, discrete cosine transform ,SVM can be used. Platform: |
Size: 225280 |
Author:nanhi |
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Description: 有了Gabor核函数后就可以采用前文中提到的“离散二维叠加和卷积”或“快速傅立叶变换卷积”的方法求解Gabor变换，并对变换结果求均值和方差作为提取的特征。32个Gabor核函数对应32次变换可以提取64个特征（包括均值和方差）。由于整个变换过程代码比较复杂，这里仅提供测试代码供下载。该代码仅计算了一个101×101尺寸的Gabor函数变换，得到均值和方差。代码采用两种卷积计算方式，从结果中可以看出，快速傅立叶变换卷积的效率是离散二维叠加和卷积的近50倍。-to extract features. 32 Gabor kernel function corresponding to 32 times transform can extract 64 characteristics (including mean and variance). Because the whole transformation process code is complicated, only provide test code for download here. This code can only calculate a 101 x 101 size of the Gabor function transform, get the mean and variance. Code USES two kinds of convolution calculation, can be seen the results, the efficiency of the fast Fourier transform (convolution is discrete two-dimensional superposition and nearly 50 times of convolution. Platform: |
Size: 1024 |
Author:丁湘燕 |
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Description: 这是一个好用的频偏估计算法的matlab仿真程序,关于非线性离散系统辨识，Gabor小波变换与PCA的人脸识别代码。- This is a useful frequency estimation algorithm matlab simulation program, Nonlinear discrete system identification, Gabor wavelet transform and PCA face recognition code. Platform: |
Size: 5120 |
Author:mxeux |
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Description: Gabor小波变换与PCA的人脸识别代码，关于非线性离散系统辨识，处理信号的时频分析。- Gabor wavelet transform and PCA face recognition code, Nonlinear discrete system identification, When processing a signal frequency analysis. Platform: |
Size: 5120 |
Author:鱼军毅 |
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Search - discrete gabor transform