deep-learn-Autoencoder_Code

能够用matlab轻松实现id3算法，对数据挖掘起到很大帮助(Easily be able to use matlab implementation id3 algorithm, data mining has played a lot of help)

神经网络PID仿真程序,直接导入MATLAB就可以运行(PID neural network simulation program directly into MATLAB on the run)

lte链路接收链路TURBO码解码matlab代码，(lte link decoding matlab code)

舰船目标的旋转运动逆合成孔径雷达成像仿真(Rotational movement of the ship target inverse synthetic aperture radar imaging simulation)

运用平面波展开法模拟光子晶体光纤中的带隙结构(The use of plane wave expansion method in photonic crystal fiber simulation of the band structures of)

说明：   本书内容深入浅出、图文并茂、理论与实训紧密结合，各章之间既相互联系又相对独立，读者可根据需要选择阅读。本书每章内容都包括两部分，一部分为理论讲解，以丰富多样的实例作为支撑；另一部分为与理论部分配套的MATLAB仿真实训，本部分与理论部分前后呼应，同时密切结合生产实践。 (The Guide book illustrations, theory and practical training closely, both among the various chapters of interconnected and relatively independent, readers may be selected to read. Content of each chapter the book consists of two parts, the theoretical explanation, to a variety of examples as support the other part is matching with the theoretical part of the MATLAB simulation training, this section with the theoretical part of the previous ones, while keeping a close with the production practice.)

产生调制信号后，提取调制信号的特征参数的matlab算法。(Generate a modulated signal, the extraction of characteristic parameters of the modulation signal matlab algorithm.)

Prueba1 FletcherReeves Hernández Santiago José Maestría en Ciencias de la Computación Septiembre / 2011 1. Comenzar con un punto arbitrario 2. Calcular Gradiente de Fi 3. Si el Gradiente Fi es igual a 0(converge), termina 4. Si el Gradiente Fi es !=0 continuar 5. Encontrar dirección de búsqueda Si= -GradienteFi= - Gradiente F(Xi) 6. Determinar la Longitud Optima del incremento lamda(i) en dirección Si X(i+1)=X(i)+lamda(i)*S(i)= X(i)-lamda(i)*Gradiente F(Xi) 7. Hacer i=2 8. Obtener Gradiente Fi 9. Calcular Si= -GradFi + ( [abs(GradFi)^2]/[abs(GradF(i-1))^2] )*S(i-1) 10. Determinar la Longitud Optima del incremento lamda(i) en dirección Si X(i+1)=X(i)+lamda(i)*S(i)= X(i)-lamda(i)*Gradiente F(Xi) 7. Verificar Optimalidad de X(i+1) Si es optimo, detener Si no es optimo hacer i=i+1 e ir al paso 8

使用吗matlab语言，实现很多模式识别上的经典算法，如Perceptron_Batch算法等(Matlab language to use it to achieve many of the classic pattern recognition algorithms, such as algorithm Perceptron_Batch)

改进节点法建立MNA方程 matlab算法，附有设计文档(Modified nodal equations matlab algorithm established by MNA)