adpcmrecoder

HRTFs functions in full mode

基于matlab编写的SQP优化算法，用来求解有约束的非线性规划问题(sequential quadratic programming:Used to solve constrained nonlinear programming problems)

协同过滤代码，由于需要，但是找不到好的代码，所以花了一天时间写的代码，希望对大家有帮助！(recommend system)

ofdmaz自适应资源分配，SIPS04Main.m为主程序，直接运行即可获得结果(ofdmaz adaptive resource allocation, SIPS04Main.m-based procedures, to receive the results of the direct operation)

N-Queen implementation in Matlab

kalman for real tracking

说明：  用于计算Delta机器人在三维空间中的工作区域(Calculating the Working Area of Delta Robot in Three-Dimensional Space)

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.)

有关心电去噪处理的论文，不错的文章，写的很仔细(Are concerned about the power denoising papers, good article, very carefully written)

该程序主要进行重力一位界面的反演，该程序精度准确,具有很好的实际应用效果。(The program mainly for gravity inversion of an interface, the program precision, with good practical results.)