road_detection

toi co the nghe nhac bang choung trinh nay

说明：  我做的用于非接触电能传输的自适应谐振技术方案，用到了MATLAB仿真，对研究非接触供电，以及学习锁相环的MATLAB仿真有很好的帮助。(Principles of Adaptive Resonance Technology for Contactless Power Transmission System，contactless, adaptive, series resonance, phase-locked loop)

使用MATLAB语言实现数字图像处理的各方面基本功能，希望对大家有用(Using the MATLAB language to implement all aspects of digital image processing basic functions, we want to be useful)

光子晶体的算法，一个关于光子晶体的比较有用的算法，还算可以用(The algorithm of the photonic crystal, a photonic crystal, the more useful algorithms, OK)

说明：  一篇很好的matlab的PDEtool工具箱使用文献.感兴趣的可以看看.(A good use of matlab toolbox of PDEtool literature. Interested can look at.)

自适应滤波算法的实现，包括LMS算法与RLS算法。能够实现自适应滤波。(Adaptive filtering algorithm, including the LMS algorithm and RLS algorithm. Adaptive filtering can be achieved.)

说明：  一个双向LSTM程序 Long Short Term 网络—— 一般就叫做 LSTM ——是一种 RNN 特殊的类型，可以学习长期依赖信息。LSTM 由Hochreiter & Schmidhuber (1997)提出，并在近期被Alex Graves进行了改良和推广。在很多问题，LSTM 都取得相当巨大的成功，并得到了广泛的使用。 LSTM 通过刻意的设计来避免长期依赖问题。记住长期的信息在实践中是 LSTM 的默认行为，而非需要付出很大代价才能获得的能力！ 所有 RNN 都具有一种重复神经网络模块的链式的形式。在标准的 RNN 中，这个重复的模块只有一个非常简单的结构，例如一个 tanh 层。(A bidirectional LSTM program Long short term network, commonly known as LSTM, is a special type of RNN that can learn long-term dependent information. LSTM was proposed by Hochreiter & schmidhuber (1997) and recently improved and promoted by Alex graves. In many problems, LSTM has achieved great success and has been widely used. LSTM is designed to avoid long-term dependency. Remember that long-term information is the default behavior of LSTM in practice, not the ability to acquire it at a great cost! All RNNs have a chained form of repetitive neural network modules. In the standard RNN, this repetitive module has only a very simple structure, such as a tanh layer.)

script en matlab ofdm/cdma

汉明码，Golay码，Reed-Muller码的仿真代码(Hamming, Golay and Reed-Muller codes source codes)

MATLAB工具结合数字图像处理，完成实验，有图像彩色空间转换，傅里叶变换，余弦变换，直方图均衡等等，有需要的看一下。(Combination of MATLAB tools for digital image processing, the completion of the experiment, the image color space conversion, Fourier transform, cosine transform, histogram equalization and so on, there is a need to look at the.)