matlab_kalmantools

一维小波降噪，该程序运用多尺度小波变换法进行降噪，效果不错(One-dimensional wavelet noise reduction, the program is the use of multi-scale wavelet transform for noise reduction and good results)

Matlab Code to suppress estimate PSD, Noise in speech and minimise it and thus improve SNR

includes various matlab files for didfeent smart antennas configurations

Mammography is one of the available techniques for the early detection of masses or abnormalities which is related to breast cancer. Breast Cancer is the uncontrolled of cells in the breast region, which may affect the other parts of the body. The most common abnormalities that might indicate breast cancer are masses and calcifications. Masses appear in a mammogram as fine, granular clusters and also masses will not have sharp boundaries, so often difficult to identify in a raw mammogram. Digital Mammography is one of the best available technologies currently being used for the early detection of breast cancer. Computer Aided Detection System has to be developed for the detection of masses and calcifications in Digital Mammogram, which acts as a secondary tool for the radiologists for diagnosing the breast cancer. In this paper, we have proposed a secondary tool for the radiologists that help them in the segmentation and feature extraction process.

本文介绍了一个新的降低ofdm中的PAPR的方法(This article describes a new reduction of the PAPR in ofdm method)

经验模态分解函数，可实现信号分解及滤波的功能。(EMD scheme which can achieve signal decomposition and noise elimanition.)

matlab的入门书籍，比较浅显，适合于初学者阅读(matlab introductory books, for less, suitable for beginners to read)

Detection of M-ary PSK signals (Detection of M-ary PSK signals)

说明：  讲述LTE技术创新与挑战的很有价值的参考资料，值得去读(About the challenges of LTE technology, innovation and valuable reference, it is worth to read)

说明：  Parzen窗法，由样本求概密估计，例为一维正态分布和双峰均匀分布，内附随机数生成的原理说明。( window method, by the sample density estimate for estimated Example for one-dimensional normal distribution and bimodal uniform distribution, random number generator containing a description of the principle.)