newton

Harmony Search Algorithm matlab code

The QSystemSemaphore class provides a general counting system semaphore for Linux.

说明：  基于模糊PID控制下的BUCK电路稳压输出的仿真，并对比了模糊控制和PID控制。(Based on the simulation of BUCK circuit voltage stabilizing output under fuzzy PID control, the fuzzy control and PID control are compared.)

this is the code written for baysian classifier that contains lda,pca, normalization

程序实现了生成决策树并使用决策树对离散特征向量进行分类。在判断是否要继续生成叶节点时采用entropy来作为impurity的measurement.(Program and use the decision tree decision tree to generate discrete feature vectors for classification. In determining whether to continue generating leaf nodes using entropy as the impurity of the measurement.)

神经网络遗传算法函数极值寻优————非线性函数极值寻优(Neural network genetic algorithm optimization function extreme nonlinear function extreme optimization)

该程序是针对智能小车躲避障碍物而设计的，小车通过检测其前方所行进道路上是否有障碍物而判断其运行路线，以能够成功躲避障碍物。(The program is designed for smart car avoid obstacles, the car through the test, the marching on the road if there are obstacles and determine the route operation, and to avoid obstacles to success. )

说明：  基于MATLAB的算法仿真实验及分析、基于DSP的硬件算法综合实验等三个层次的实践活动，帮助同学进一步领会和深化课堂上学到的有关数字信号处理的基本概念、基本原理以及基本的信号处理操作(algorithm based on MATLAB simulation and analysis DSP-based algorithms integrated hardware experiments three levels of practice, to further help students understand and deepen the classroom to the digital signal processing of the basic concepts the basic principles and basic signal processing operation)

很多解方程的经典matlab例程，欢迎有需要的童鞋来下载~~~·(Solving equations matlab many classic routines, welcomed the children s shoes need to download ~ ~ ~*)

用积分最小值准则来求P,PI,PID的个参数，其中Gc是校正器的传递函数,kp为比例系数， Ti为积分时间常数，Td为微分时间常数，输入参量vars为带迟滞--惯性环节模型的[K T τ]，已知参数k=vars（1）；T=vars（2）；ι=vars（3）,iC=vars(4) (Minimum criteria of integral seeking P, PI, PID' s parameters, which Gc is the corrector transfer function, kp is proportional coefficient, Ti for the integral time constant, Td for the differential time constant, input parameters vars as with hysteresis- inertia model of [KT τ], known parameters k = vars (1) T = vars (2) ι = vars (3), iC = vars (4) )