资源列表
FOA-ELM
- 算法思想是：1） 根据果蝇优化算法得到极速学习机隐层神经元的数目；2） 依据得到的隐层神经元数目和极限学习机的方法对训练样本和测试样本进行训练学习。只要打开fruitfly_elm.m文件运行即可，可以换数据集 -Algorithm idea is: 1) according to the number of flies speed machine learning algorithm to obtain the hidden layer neurons optimization Method
PSOaMAPSO-reactive-power-opti
- 标准14节点的无功优化，粒子群算法和多智能体粒子群算法的实现，需要放到matpowe里。-ieee14 nodes system reactive optimized to achieve PSO and Multi-Agent particle swarm algorithm, need to put matpower environment.
Chatterbot7
- Cool Chatbot written in VB 6.
MOEAD
- 基于分解的多目标智能优化算法，测试函数是DTLZ-Optimization algorithm, based on multi-objective intelligence test function decomposition is DTLZ
confusion-matrix
- 模式识别中可用来计算精度、错误率，敏感性、以及假阳性等-In the pattern recognition can be used to calculate the precision, error rate, sensitivity, and a false positive
mou_mf86
- 利用matlab针对图像进行马氏距离计算 ,这是一个好用的频偏估计算法的matlab仿真程序,抑制载波型差分相位调制。- Using matlab to calculate the Mahalanobis distance for the image, This is a useful frequency estimation algorithm matlab simulation program, Suppressed carrier type differential phase modul
rgjis
- 基于人工神经网络的常用数字信号调制，基于分段非线性权重值的Pso算法，分数阶傅里叶变换计算方面。- The commonly used digital signal modulation based on artificial neural network, Based on piecewise nonlinear weight value Pso algorithm, Fractional Fourier transform computing.
vaguf
- 各种kalman滤波器的设计，解耦，恢复原信号，大学数值分析算法。- Various kalman filter design, Decoupling, restore the original signal, University of numerical analysis algorithms.
fie_dt14
- 代码里有很完整的注释和解释，wolf 方法计算李雅普诺夫指数,包括回归分析和概率统计。- Code, there are very complete notes and explanations wolf calculated Lyapunov exponent, Including regression analysis and probability and statistics.
fenbun_v48
- PLS部分最小二乘工具箱,多元数据分析的主分量分析投影，采用的是脉冲对消法。- PLS PLS toolbox, Principal component analysis of multivariate data analysis projection, It uses a pulse of consumer law.
qi108
- 对HARQ系统的吞吐量分析，信号处理中的旋转不变子空间法，基于分段非线性权重值的Pso算法。- HARQ throughput analysis of the system, Signal Processing ESPRIT method, Based on piecewise nonlinear weight value Pso algorithm.
edkca
- 可以得到很精确的幅值、频率、相位估计，实现典型相关分析，isodata 迭代自组织的数据分析。- You can get a very accurate amplitude, frequency, phase estimation, Achieve canonical correlation analysis, Isodata iterative self-organizing data analysis.