leeedge

breast cancer detection

数字助听器中多通道响度补偿方法的研究.pdf(Multi-channel digital hearing aid loudness compensation method. Pdf)

学习电力电子必须完成仿真，三相不可控整流电路的MATLAB仿真(Learning must be completed power electronics simulation, three-phase controlled rectifier circuits MATLAB simulation)

2D particle movement in a circle domain

对二元序列10110010，画出2FSK的波形，其中载波频为码元速率的2倍。(For binary sequence 10110010, draw waveform 2FSK, where the carrier frequency of 2 times the symbol rate.)

希尔伯特黄变换的程序源码，可用于各种信号分析处理(Hilbert Huang Transform source of procedures that can be used to deal with a variety of signal analysis)

RLS自适应数字预失真算法Matlab仿真，仿真通过，比较少见的资料，仅供学习交流(Matlab simulation of RLS adaptive digital distortion algorithm for PA)

FMCW Radar system : Detection and tracking the target in radar system ( new technology )

本代码给出了一个不敏卡尔曼滤波实例和不敏卡尔曼滤波算法代码(This code gives an Unscented Kalman filter instance and not Unscented Kalman filter algorithm code)

多目标优化 相对传统多目标优化方法, PSO在求解多目标问题上具有很大优势。首先, PSO的高效搜索能力有利于得到多目标意义下的最优解 其次, PSO通过代表整个解集的种群按内在的并行方式同时搜索多个非劣解,因此容易搜索到多个Pareto 最优解 再则, PSO的通用性使其适合于处理所有类型的目标函数和约束 另外, PSO 很容易与传统方法相结合,进而提出解决特定问题的高效方法。就PSO 本身而言,为了更好地解决多目标优化问题,必须解决全局最优粒子和个体最优粒子的选择问题(Compared with the traditional multi-objective optimization of multi-objective optimization method, PSO in solving multi-objective problem has a great advantage. First, PSO is conducive to the efficient search capabilities are more objective sense of the optimal solution Secondly, PSO representative of the entire solution set through the population by way of the inherent parallel search multiple non-inferior solution, and this can easily search for the most number of Pareto optimal solution Furthermore, PSO' s versatility make it suitable for handling all types of objective function and constraints addition, PSO is easy to integrate with the traditional method, and then propose an efficient way to solve specific problems. The PSO itself, in order to better address the multi-objective optimization problems, the need to address the global best particle and the individual selection of the optimal particle)