预测控制MAC一阶无延迟

用于提取心音包络的程序，编译运行较好，有界面显示。(Used to extract the heart sound envelope program, compile and run better, there are screen displays.)

说明：  MATLAB小波分析___张德丰——源代码，对于学习小波分析很有帮助。(MATLAB Wavelet Analysis)

说明：  本书是“移动通信前沿技术系列”之一，全书共分18个章节，主要对协作通信及网络知识作了介绍，具体内容包括空时分集和编码、空时频分集与空时频编码、中继信道及协议、单中继协作通信、多节点协作通信等。全书内容分为三部分，第一部分回顾传统的MIMO系统，介绍空间、时间、频率分集的概念。第二部分主要考虑协作通信物理层的关键问题，并对其提出了行之有效的解决方案，比如针对协作通信的分布式特点，提出分布式空时(频)码；针对协作通信的频谱效率问题，提出了新颖和有效的协作方案。第三部分介绍协作通信对物理层之上的MAC层、网络层及应用层产生的影响，内容涉及如何协作路由，如何通过协作使网络覆盖范围增大，如何延长网络寿命等。(This book is one of the "cutting edge mobile communication technology series". The book is divided into 18 chapters, mainly on cooperative communications and network knowledge and specific content including the empty hours of collection and coding, space-time-frequency diversity and space-time frequency coding, relay channel and protocols, single-relay cooperative communication, multi-node cooperative communications.)

music算法在谱估计中的matlab程序 (music spectrum estimation algorithms in the Matlab procedures)

Matlab Code for: Removing the Blocking Artifacts of Block-Based DCT Compressed Images in IEEE TRANSACTIONS ON IMAGE PROCESSING, VOL. 12, NO. 7, JULY 2003

图像分析与识别，从一副包含各种动物的图像中识别出想要的动物(Image analysis and recognition)

超宽带（UWB）的多频带OFDM与定点transmitterreceiver物理层建模 UWB的分析 超宽带的BPSK分析 第五阶导数的BPSK超宽带 超宽带信道模型 超宽带链接分析 超宽带单环 超宽带单脉冲 超宽带多旋回(Ultra-wideband (UWB) multiband OFDM physical layer with fixed-point transmitterreceiver modeling analysis of UWB UWB BPSK Fifth Order Derivative analysis of BPSK UWB UWB UWB channel model for UWB link analysis of UWB single-loop single-pulse ultra-wideband polycyclic)

说明：  这是一个LMBP算法的源程序MATLAB(THIS IS A LMBP PROGRAM)

This file is regarding MATLAB, which describes the different models in MATLAB simulation or block which are present and useful for different applications.

压缩感知方法演示，1-D信号压缩传感的实现(正交匹配追踪法Orthogonal Matching Pursuit) 测量数M>=K*log(N/K),K是稀疏度,N信号长度,可以近乎完全重构(1-D signal is compressed sensing to achieve (orthogonal matching pursuit method Orthogonal Matching Pursuit) number of measurements M> = K* log (N/K), K is the sparsity, N signal length, can be almost completely reconstructed)