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《MATLAB时尚百例实例》实例84-1()

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.)

该matlab函数用于计算雷达信号的模糊函数图、距离模糊函数图和速度模糊函数图(failed to translate)

cell model solar using in photovoltaics system

EOF分解，用ncdisp命令可以看到HadISST_sst.nc是1870年1月至最近的全球SST数据，按比例截取北太平洋（20N-80N 130E-90W）1971年1月至1990年12月240个月份的SST数据进行经验正交函数（Empirical Othorgnal Function）分解,简记为EOF分解，得到该区域该时段的海温时空特征。(EOF decomposition, with ncdisp command can see HadISST_sst.nc is January 1870 to the recent global SST data, in proportion to the interception of the North Pacific (20N-80N 130E-90W) 1971 年 1 月 至 1990 年 12 月 240 month SST data, empirical orthogonal function (Empirical Othorgnal Function) decomposition, abbreviated as EOF decomposition to obtain spatial and temporal characteristics of sea surface temperature in the region of the period.)

optimal power flowoptimal power flowoptimal power flowv

This is a MATLAB implementation of the SIFT detector and descriptor

稀疏性最小二乘支持向量机，针对最小二乘支持向量机缺少稀疏性的问题，以特征提取为基础提出具有稀疏性解的最小瓶二乘支持向量机(Sparsity LSSVM for LSSVM lack sparsity issues to feature extraction is proposed based on the solution of sparse least squares support vector machine bottle)

航迹起始算法代码，用于实现简单航迹逻辑的算法(logical algorithm for Track initiation)

pixel based image fusion