gabor_face

3.7 寸屏幕 控制电力板 大家可以学习学西 包准能用的(3.7-inch screen control panels you can learn to learn West'll usable)

matlab入门易学教程，通俗，易懂，很适合新手学习(Started to learn matlab tutorial, popular, easy to understand, it is suitable for beginners to learn)

dynamic voltage restorer by dq0 control system

主动降噪算法集合,active noise reduction(active noise reduction)

morphological operations on images

说明：  摘要：简述信道编码理论，详细说明分组码的编译原理、实现方法及检错纠错能力，用MATLAB仿真有无信道编码条件下对通信系统性能的影响及信道编码在不同信道下对通信系统性能的影响，如AWGN信道和深衰落信道。 关键词：信道编码、分组码、MATLAB仿真、性能 (Abstract: This paper describes channel coding theory, the detailed block code compiler theory, implementation method, and error detection and correction capabilities, with the MATLAB simulation without channel coding conditions on the communication system performance and channel coding in the different channels of communication systems properties, such as deep fading channel and AWGN channel. Keywords: channel coding, block codes, MATLAB simulation, performance)

阐述了负荷预测的应用研究,Matlab实现界面友好，欢迎大家下载学习，是机器学习的例程，包含优化类的几个简单示例程序，最终的权值矩阵就是滤波器的系数。( It describes the application of load forecasting, Matlab to achieve user-friendly, Welcome to download the study, Machine learning routines, Optimization class contains several simple sample programs, The final weight matrix is ??the filter coefficient.)

该软件包包含了合并执行在MATLAB9升-1的最小化算法。每个函数都使用一组参数是一致的（如停止准则和公差）与我们的基准脚本接口。 正交匹配追踪：SolveOMP.m 原对偶内点法：SolvePDIPA.m 梯度投影：SolveL1LS.m 同伦：SolveHomotopy.m 迭代阈值：SolveSpaRSA.m 近梯度：SolveFISTA.m TFOCS：SolveTFOCS.m SesopPCD：SolveSesopPCD.m 原始增强拉格朗日乘子：SolvePALM.m 双增广拉格朗日乘子：SolveDALM.m SolveDALM_fast.m(The package contains L1 minimization algorithm. such as SolveSpaRSA.m、SolveFISTA.m)

说明：  压缩感知（Compressed sensing），也被称为压缩采样(Compressive sampling)，稀疏采样(Sparse sampling)，压缩传感 [1] 。它作为一个新的采样理论，它通过开发信号的稀疏特性，在远小于Nyquist 采样率的条件下，用随机采样获取信号的离散样本，然后通过非线性重建算法完美的重建信号 [1] 。压缩感知理论一经提出，就引起学术界和工业界的广泛关注。(Compressed sensing (Compressed sensing), also known as compression sampling (Compressive from), Sparse sampling (Sparse from), Compressed sensing [1].As a new sampling theory, it develops the sparse characteristics of signals, obtains the discrete samples of signals with random sampling under the condition that the sampling rate is much lower than Nyquist sampling, and then perfectly reconstructs the signals through the nonlinear reconstruction algorithm [1].Once the theory of compressed sensing was put forward, it attracted extensive attention from academia and industry.)

Dataset for Text Detection and Extraction