Based-on-BP-power-load-forecasting

说明：  基于模拟退火的粒子群算法，基于自然选择的粒子群算法，基于杂交的粒子群算法(Based on simulated annealing particle swarm algorithm, based on natural selection, particle swarm optimization, particle swarm optimization based on hybrid)

this file is optimization with genetic algorithm

说明：  蒙特卡罗方法可以有效地解决复杂的工程问题，而MATLAB具有强大的数值计算功能。将二者结合使用，可以得到高效的解决问题的方法。本文阐述了该方法并通过实例验证了该方法的正确性和优越性。 (Monte Carlo method can effectively solve complex engineering problems, and MATLAB has powerful function of numerical calculation. The two in combination, can be cost-effective solution to the problem. This paper describes the methods and examples of the method to verify the correctness and superiority.)

基于Matlab环境下的OQPSK QPSK系统仿真(Of OQPSK QPSK system simulation based on Matlab environment)

Matlab 实用小程序100例。 都是很常用的，适合初学者。(100 cases of the Matlab practical applets. They Are very common for beginners.)

IMAGE COMPRESSION USING DISCRETE WAVELET AND DISCRETE COSINE TRANSFORM

BPSK_QPSK LDPC基于MATLAB编译码仿真程序(BPSK_QPSK LDPC)

patch antenaa fdtd.. mkldnkdjgsircdo,gudficghfoidgjsdcmhgrig

说明：  本书从MATLAB仿真的角度出发，系统地介绍了系统辨识与自适应控制的基本理论和方法。本书共6章，主要内容为：绪论、系统辨识、模型参考自适应控制、自校正控制（包括广义预测控制）、基于常规控制策略的自校正控制和非线性系统辨识与控制（包括神经网络和模糊控制）。书中每种算法都配有仿真实例、仿真程序、仿真结果以及对仿真结果的简要分析，以便于读者深入理解和运用基本理论和算法(From the perspective of MATLAB simulation, this book systematically introduces the basic theories and methods of system identification and adaptive control. This book has 6 chapters, the main contents are: introduction, system identification, model reference adaptive control, self-tuning control (including generalized predictive control), self-tuning control based on conventional control strategies, and identification and control of nonlinear systems (including neural network) And fuzzy control). Each algorithm in the book is equipped with simulation examples, simulation programs, simulation results, and a brief analysis of the simulation results, so that readers can deeply understand and use basic theories and algorithms.)

该程序实现时域LMS算法，并用统计的方法仿真得出不同步长下的收敛曲线(The program to achieve time-domain LMS algorithm, and simulation statistics do not come under the simultaneous convergence of a long curve)