RBF

说明：  matlab阵列信号处理MVDR程序，高分辨方位估计从事人员可供参考。(matlab array signal processing MVDR procedures, personnel engaged in high-resolution DOA estimation for reference.)

几个简单的空域滤波器程序，包括Guassian、laplace和unsharp(A few simple spatial filter process, including the Guassian, laplace and unsharp)

说明：  根据设计指标提取广义切比雪夫滤波器阶数和传输零点位置，参照《新型微波滤波器的理论与设计》_褚庆昕一书，并提供了滤波器耦合矩阵的计算程序，参照Richard Cameron的方法。(The order of the generalized Chebyshev filter and the position of the transmission zero point are extracted according to the design indicators. Refer to the book "Theory and Design of New Microwave Filters" _ Chu Qingxin, and provide a calculation program for the filter coupling matrix.)

图像对数极坐标转换，matlab源码。简单，实用(Log-polar coordinate conversion image, matlab source code. Simple, practical)

本程序主要是应用到无线传感器网络目标定位与追踪中，通过利用MUSIC算法来测量接受信号的波达方向角DOA，然后进一步定位与追踪。(This procedure is mainly applied to wireless sensor networks, targeting and tracking, the MUSIC algorithm is used to measure the signal direction of arrival angle DOA, then locate and track.)

理想低通滤波器滤波器截止角频率wc，阶数Me(filter function hd=ideal_lp(wc,Me))

matlab时频分析配套源码第3章的程序，请大家共享(Matlab time-frequency analysis supporting source Chapter 3, please share)

Performance analysis of steganography is done for selecting better wavelet for application by analyzing Peak Signal Noise Ratio(PSNR) of different wavelet families like Haar, Daubechies, Biorthogonal, Reverse Biorthogonal & Meyer wavelet(dmey) on result oriented basis using Matlab environment.

针对风电场短期风速的预测提出一种基于小波变换的组合预测方法。首先利用Mallat 算法对短期风速时间序列进行db3 小波三层分解与重构，得到短期风速时间序列的近似分量和细节分量。针对近似分量和细节分量的不同特性，对近似分量利用粒子群算法优化的最小二乘支持向量机进行预测，对细节分量利用自回归求和滑动平均模型进行预测。最后各预测模型预测值组合叠加得到最终的短期风速预测值。仿真结果表明该方法具有较高的预测准确度。(In order to improve short-term wind speed prediction accuracy of wind farms，a combined prediction method based on the wavelet transform is proposed. Firstly，the db3 wavelet is used for three-layer decomposition and reconstruction for short-term wind speed time series through Mallat algorithm. The approximation components and the detail components of the short-term wind speed are then obtained. Next，according to the different characteristics of these components，the least square support vector machine optimized by particle swarm algorithm and the autoregressive integrated moving average model are adopted as the predictivemodels for the approximate components and the detail components respectively. Then，the final predictive value of the short-term wind speed is obtained by the combination of the two components. The simulation results indicate that higher accuracy can be obtained in this prediction method.)

自适应波束形成多种算法的matlab实现，算法类型：MVDR,LCEC,GSC,PCI,MWF,PCA-MVB,SC-MVB,EC-A (A variety of adaptive beamforming algorithm matlab implementation, algorithm type: MVDR, LCEC, GSC, PCI, MWF, PCA-MVB, SC-MVB, EC-A)