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BPexample
- 开发环境:Matlab 简要说明:动量-自适应学习调整算法。在实际应用中，原始的BP算法很难胜任，因此出现了很多的改进算法。BP算法的改进主要有两种途径，一种是采用启发式学习方法，另一种则是采用更有效的优化算法。本例采用动量BP算法，来实现对网络的训练过程，动量法降低了网络对于误差曲面局部细节的敏感性，有效地抑制网络陷于局部极小。-development environment : Matlab Brief Descr iption
ReversibleJumpMCMCSimulatedAnneaing
- This demo nstrates the use of the reversible jump MCMC simulated annealing for neural networks. This algorithm enables us to maximise the joint posterior distribution of the network parameters and the number of basis fun
Facts__Conjectures__and_Improvements_for_Simulated_Annealing
- 模拟退火优化算法 Simulated annealing is a simple and general algorithm for finding global minima. It operates by simulating the cooling of a (usually fictitious) physical system whose possible energies correspond to the values o
BPexample
- 开发环境:Matlab 简要说明:动量-自适应学习调整算法。在实际应用中，原始的BP算法很难胜任，因此出现了很多的改进算法。BP算法的改进主要有两种途径，一种是采用启发式学习方法，另一种则是采用更有效的优化算法。本例采用动量BP算法，来实现对网络的训练过程，动量法降低了网络对于误差曲面局部细节的敏感性，有效地抑制网络陷于局部极小。-development environment : Matlab Brief Descr iption
ReversibleJumpMCMCSimulatedAnneaing
- This demo nstrates the use of the reversible jump MCMC simulated annealing for neural networks. This algorithm enables us to maximise the joint posterior distribution of the network parameters and the number of basis fun
chaos
- 一种改进的混沌优化，便尺度混顿优化的优势在于速度快，不容易掉入局部极小-An improved chaos optimization, then mixed Dayton-scale optimization has the advantage of being fast, not easy to fall into local minima
chaosResearch
- 便尺度混沌优化，方法很简单，但是速度快，不易局部极小-Will scale chaos optimization method is simple, but fast, easy local minima
Atoolbox
- A collection of functions is presented which includes 2nd generation wavelet decomposition and reconstruction tools for images as well as functions for the computation of moment invariants. The wavelet schemes rely on th
huangjin
- 最优化中的实例，利用黄金分割法求出下单峰函数极小点-Optimization of the examples, the use of golden section method are obtained under the single-peak function minima
EMDduandianchuli
- 利用神经网络分析方法对一个给定信号的两端进行延拓，在数据的两端各得到两个附加的极大值点和两个附加的极小值点.由此利用三次样条函数得到原始信号的上下包络线和平均包络线，实现了准确的EMD分解. -The use of neural network analysis of a signal at the two ends of a given extension to the data obtained at the two ends
SimulatedAnnealing
- Simulated Annealing (SA) is a smart (meta)-heuristic for Optimization. Given a cost function in a large search space, SA replaces the current solution by a random "nearby" solution. The nearby solution is chosen with a p
steepest_method_with_const_step
- NUMERICAL OPTIMIZATION: This steepest descent method with constant step length to find the minima of f(x, y) = xy exp(− 2x^2 − y^2 + 0.3y) Graphical represxentation in 5 ways of solution, simple and clea
PARS.cpp
- Program for finding minima of functions of several variables, several methods (Powell, Polak-Riber, Pearson, etc.)
ShuLex
- Program for finding minima of functions of several variables, several methods with GUI.
peakdet
- Peak detection is one of the most important time-domain functions performed in signal monitoring. Peak detection is the process of finding the locations and amplitudes of local maxima and minima in a signal that satisfie
MinMaxFilterFolder
- Min/Max filter，最大最小滤波器，说明看英文，只是国外的人写的代码， -Descr iption The filter computes the minima and/or maxima of an array over sliding window with a given size. Multidimensional array is fully supported: running filter in 1
29175-29175.ZIP
- Mathematical methods are an alternative to tackle visual perception. The central idea behind these methods is to reformulate the visual perception components as optimization problems where the minima of a specificall
10.1.1.3.8227
- Noise Estimation by Minima Controlled Recursive Averaging for Robust Speech Enhancement
local_minmaxcpp
- fast 1d and 2d local minima detector
newton2
- nonlinear optimization code can find local or global minima