资源列表
chirp
- 该程序实现了chirp信号的二进制调制及匹配滤波解调，并且求解出了调制的chirp信号通过AWGN信道后的误码率-The program realizes the chirp signal binary modulation and matched filter demodulation, and the solution of the chirp signal through the AWGN channel after the error rate
MSc---Hardware-JPEG-Decompression
- Due to the ever increasing popularity of mobile devices, and the growing number of pixels in digital photography, there becomes a strain on viewing one s own photos. Similar to Desktop PCs, a common trend occurring in the mobile market to com-
MSc---Orthogonal-vs-Biorthogonal-Wavelets-for-Ima
- E ective image compression requires a non-expansive discrete wavelet transform (DWT) be employed consequently, image border extension is a critical issue. Ideally, the image border extension method should not introduce distortion under compressio
intrans
- s函数的一个实例，对于学习S函数的同学有很大帮助~-s fuction
Signal-spectrum
- 矩形波函数，计算其频谱，幅度谱和相位谱，与理论值比较。-Rectangular wave function, the calculation of its spectrum, amplitude spectrum and phase spectrum, compared with the theoretical value.
wavelet-fast-calculation
- 小波快速计算的仿真例子-The simulation example of wavelet fast calculation
ECG-signal-denoising
- 在心电信号处理过程中，为了避免产生Gibbs 振荡现象和严重的频率混叠现象，提出一种基于双树复小波变换，并结合最大后验估计确定阈值的心电信号去噪方法。文中采用了信噪比和均方误差来评价双树复小波变换和离散小波变换两种方法对心电信号的去噪效果。实验结果表明: 与传统离散小波变换相比，双树复小波变换去噪更彻底，边界、纹理等特征能较好地保留，可以作为一种生物医学信号降噪处理的新方法。-In ECG signal processing， in order to avoid the phenomena of
t03.m
- 模拟信号加噪声，设计FIR滤波器滤除噪声-Analog signal plus noise, design FIR filter to filter noise
bfilter
- 双边滤波，用于图像预处理后。效果很不错~可以直接调用。-Bilateral Filtering for after image preprocessing. The effect is very good- can be called directly.
MATLAB
- 手动实现的哈尔小波变换，没有借用外部库,如有问题请回复-haar wave transform
exa100701
- 利用小波分离对信号进行去噪，可用于分析采用不同去噪方式时效果对比，也可观察采用不同小波时的效果。-The signal denoising using wavelet separation can be used to analyze the effect comparison when using different denoising methods, and also observe the effect when using different wavelet.
wavelet_dec
- 利用小波分离对信号进行分解重建，观察采用不同小波时的效果，当分解次数增多时，重建效果越好。-The wavelet transform is used to decompose and reconstruct the signal, and the effect of different wavelet is observed. When the number of decompositions increases, the reconstructed effect is better.