资源列表
[matlab例程] signal-sampling-MATLAB
说明:基于MATLAB的信号采样与重构的实现,该文档是基于理论算法的研究,同时给出了较为详细的说明。-Realization of signal sampling and reconstruction based on MATLAB<BAOYANBO> 在 2025-08-26 上传 | 大小:123kb | 下载:0
[matlab例程] frit_toolbox
说明:codes for finite continuous ridgelet transform<arpit> 在 2025-08-26 上传 | 大小:61kb | 下载:0
[matlab例程] beamforming
说明:利用lms自适应滤波器原理,实现波束形成。 波束形成器的零干扰容量随着迭代次数和干扰目标信号比的增大而改善。-Lms adaptive filter using the principle to achieve beamforming. Beamformer with the zero-interference capacity of the number of iterations and the target signal interference ratio increased to<刘> 在 2025-08-26 上传 | 大小:2kb | 下载:0
[matlab例程] design-filter-to-minimum-noise
说明:根据加噪声的音乐信号,设计合适的滤波器,对原有信号进行滤波,去除噪声,实现滤波功能。-According to the signal plus noise music, design the appropriate filter, the original signal is filtered to remove noise, the filtering function.<刘> 在 2025-08-26 上传 | 大小:14kb | 下载:0
[matlab例程] Rosenbrock
说明:The Rosenbrock function is a non-convex function used as a performance test problem for optimization algorithms introduced by Rosenbrock (1960). It is also known as Rosenbrock s valley or Rosenbrock s banana function. The global minimum is insid<suci ariani> 在 2025-08-26 上传 | 大小:1kb | 下载:0
[matlab例程] junhengqi-realized
说明:利用LMS自适应滤波器原理实现均衡器的设计。并对不同N时的滤波器进行比较-The use of LMS adaptive equalizer filter to achieve the principle<刘> 在 2025-08-26 上传 | 大小:1kb | 下载:0
[matlab例程] steepdes
说明:In mathematics, the method of steepest descent or stationary phase method or saddle-point method is an extension of Laplace s method for approximating an integral, where one deforms a contour integral in the complex plane to pass near a stationary po<suci ariani> 在 2025-08-26 上传 | 大小:1kb | 下载:0
[matlab例程] kernel
说明:In computing, the kernel is the main component of most computer operating systems it is a bridge between applications and the actual data processing done at the hardware level. The kernel s responsibilities include managing the system s resources (th<suci ariani> 在 2025-08-26 上传 | 大小:5kb | 下载:0
[matlab例程] pso
说明:In computer science, particle swarm optimization (PSO) is a computational method that optimizes a problem by iteratively trying to improve a candidate solution with regard to a given measure of quality. PSO optimizes a problem by having a population<suci ariani> 在 2025-08-26 上传 | 大小:2kb | 下载:0