搜索资源列表
Matlabautofocus
- 这是我毕设做自动调焦仿真实验时，编写的自动调焦函数的Matlab代码，把基于灰度梯度的调焦函数都仿真了-This is what I do complete auto-focus based simulation experiments, the preparation of the automatic focusing function of the Matlab code, the gray gradient-based simulation of the focusing function
grade
- 设有一基于格型梯度算法的预测器，其输入 由的AR模型产生，本程序可以得出自适应预测器的曲线-There is a gradient algorithm based on the lattice of the predictor, the input generated by the AR model, the procedure can be drawn Curve Adaptive Predictor
chap3_02_MIT_MRAC
- 基于梯度法（MIT-MRAC）的模型参考自适应控制的程序-Gradient-based method of model reference adaptive control procedures
tdh
- matlab 图像梯度化示列，对新手学习matlab很有帮助-matlab image gradient-based show out on the novice to learn matlab helpful
jcs44341-344
- The mobile robot has to find the optimal path which reduces the number of steps to be taken between the starting point and the target ending point. GAs can overcome many problems encountered by traditional search techniques such as the gradient
optimization
- Derivative-based Optimization using The Gradient Descent
MATLAB
- 基于MATLAB的共轭梯度BP算法在函数逼近中的实例-MATLAB-based conjugate gradient BP algorithm in the example of function approximation
Analytical-Gradient-Based-Optimization-Technique.r
- 应用共轭梯度法综合优化交叉耦合滤波器。参考文献<Synthesis of Cross-coupled’Resonator Filters Using an Analytical Gradient-Based Optimization Technique >Smain Amari-Synthesis of Cross-coupled’Resonator Filters Using an Analytical Gradient-Based Optimization Technique _
TX_TD_PP_CORR2
- 基于边缘梯度的图像匹配，实现对寻找块图像的精确寻找-Gradient based edge image matching, to achieve the exact image of the search block to find
edge
- 运用Matlab对图像进行边缘检测，有具体的边缘检测方法，像基于梯度的算法。-Matlab, the image edge detection, edge detection method specific, such as gradient-based algorithm.
OC_2010_fusion
- 多焦点图像融合 利用基于双边梯度的锐化标准 相当对应的论文是J. Tian, L. Chen, L. Ma and W. Yu, "Multi-focus image fusion using a bilateral gradient-based sharpness criterion,"-This is a demo program of the paper J. Tian, L. Chen, L. Ma and W. Yu, "Multi-focus image fusion usi
chap3_03_MIT_MRAC_Standard
- 关于基于梯度归一化的模型参考自适应的一个m文件-Gradient-based normalization on the model reference adaptive file a m
chenxiaocen
- 盲信号分离(BSS)指在源信号混合和传输信道未知的情况下，只利用接收天线的输出观测混合信号抽取源信号的方法。本文简要阐述了常用的瞬时混合盲信号分离的LMS与RLS自适应算法，对RLS自适应算法重点研究分析了基于普通梯度与自然梯度的两种算法，并通过仿真实验来分析比较几种方法的性能。-Blind signal separation (BSS) refers to the source signal and transmission channel mixing unknown circumstanc
amga.cec09
- hybrid Archive-based Micro Genetic Algorithm (AMGA) on a set of bound-constrained synthetic test problems is reported. The hybrid AMGA proposed in this paper is a combination of a classical gradient based single-objective optimization algorithm a
AMGA
- hybrid Archive-based Micro Genetic Algorithm (AMGA) on a set of bound-constrained synthetic test problems is reported. The hybrid AMGA proposed in this paper is a combination of a classical gradient based single-objective optimization algorithm
BlindSignalAdaptiveAlgorithms
- 针对瞬时混合盲信号分离的自适应算法进行调研和比较，对于LMS，RLS算法（包括基于普通梯度和自然梯度两种）进行仿真验证，并对一些未知图像的混合进行分离。-Blind signal separation for instantaneous mixture algorithm for adaptive research and comparison, for the LMS, RLS algorithms (including gradient and natural gradient based
CS_OMP
- cs的omp恢复算法,使用恢复矩阵，观测矩阵-The physics of compressive sensing (CS) and the gradient-based recovery algorithms are presented. First, the di® erent forms for CS are summarized. Second, the physical meanings of coherence and measurement are given. Th
conjugate-gradient
- 两个程序，基于共轭梯度的BP算法，和标准的BP算法，两个都是实现函数逼近-Two procedures, based on the conjugate gradient BP algorithms, and standard BP algorithm, are both function approximation
image-segmentation
- 图像分解算法，四种方法可选，包括threshold, K means threshold, region growing以及gradient based segmentation-Image decomposition algorithm, four methods available, including the threshold, K means threshold, region growing and gradient based segmentation
conjugate gradient
- 基于Armijo-Goldstein准则的用matlab实现的共轭梯度优化方法，个人编写，适合优化方法入门练习。(Based on the Armijo-Goldstein criterion, the conjugate gradient optimization method implemented by Matlab is written by individual, suitable for the introduction of the optimization method)