MFCC

Project Management with the IBM(R) Rational Unified Process

This the solution manual for modern signal processing.

用高斯赛德尔迭代法解椭圆型方程，这是一种差分解法(High Sisaideer iterative method for solving elliptic equations, which is a differential solution)

matlab 最优化处理的一些简单编程，以及附带若干个例子(Some simple matlab program optimization, and with some examples)

偏最小二乘法工具包8.1.1版本（m文件，免安装），Eigenvector Research公司出品(PLS_Toolbox software is the world’s most extensive suite of essential and advanced chemometric multivariate analysis tools for use within the MATLAB® computational environment. )

说明：  基于MATLAB的信号处理，2FSK的产生和解调(Signal processing based on MATLAB, generation and demodulation of 2FSK)

说明：  EKF仅仅利用了非线性函数Taylor展开式的一阶偏导部分（忽略高阶项），常常导致在状态的后验分布的估计上产生较大的误差，影响滤波算法的性能，从而影响整个跟踪系统的性能。最近，在自适应滤波领域又出现了新的算法——无味变换Kalman滤波器（Unscented Kalman Filter-UKF）。UKF的思想不同于EKF滤波，它通过设计少量的σ点，由σ点经由非线性函数的传播，计算出随机向量一、二阶统计特性的传播。因此它比EKF滤波能更好地迫近状态方程的非线性特性，从而比EKF滤波具有更高的估计精度。 (EKF only uses non-linear function of the first-order Taylor expansion of some partial derivatives (ignoring higher order terms), often leading to the posterior distribution of the state estimates to generate large errors affect the performance of filtering algorithms, which affect the whole tracking system performance. Recently, the field of adaptive filtering algorithms and the emergence of new- and tasteless transform Kalman filter (Unscented Kalman Filter-UKF). EKF UKF filter is different from the idea that it points through the design of a small amount of σ by σ point spread through the nonlinear function to calculate the random vector first and second order statistical properties of the transmission. Therefore it is better than the EKF filter nonlinear characteristics equation of state approach, which is more than the EKF filter estimation accuracy.)

对leach算法进行仿真，主要是leach的分簇路由算法(Algorithm is simulated on the leach. the main is cluster routing algorithm )

对于智能天线的设计仿真 包含有详细的说明(for smart antenna design simulation contains detailed explanation)

这是线形系统理论中的同步混沌问题 虽然很简单 但有利于我们理解混沌的内容及方法(Chaos of MATLAB problems about line system )