Diagrama_Array_Tonpilz

Frame interpolation, frame rate up-conversion (FRUC), motion estimation, motion-compensated frame interpolation (MCFI), motion-compensated temporal frame interpolation (MCTFI), predictive search, true-motion, video processing

Principal component analysis (PCA) is a popular tool for linear dimensionality reduction and feature extraction. Kernel PCA is the nonlinear form of PCA, which is promising in exposing the more complicated correlation between original high-dimensional features. In this paper, we first talk about the basic ideas of PCA and kernel PCA, and then focus on the reconstruction of pre-images for kernel PCA. We also give an introduction on how PCA is used in active shape models (ASMs), and discuss how kernel PCA can be applied to improve traditional ASMs. Then we show some experiment results to compare the performance of kernel PCA and traditional PCA for pattern classification. We also implement the kernel PCA-based ASMs, and use it to construct human face models.

说明：  关于UFO显著性检测算法的实验代码（仅学习用）(Experimental code of UFO significance detection algorithm)

matlab获取PCA特征的小程序，适合初学者(matlab access characteristics of a small PCA procedures, suitable for beginners)

资料中包含利用校验子（错误图样）译码的原理、编码流程图以及matlab的编码，程序中配有注释，通俗易懂。(Information contained in the use of sub-parity (error pattern) decoding principle, flow charts and coding matlab code, the program with notes, easy to understand.)

说明：  经验模态分解（Empirical Mode Decomposition，简称EMD))方法被认为是2000年来以傅立叶变换为基础的线性和稳态频谱分析的一个重大突破，该方法是依据数据自身的时间尺度特征来进行信号分解，无须预先设定任何基函数。这一点与建立在先验性的谐波基函数和小波基函数上的傅里叶分解与小波分解方法具有本质性的差别。(Empirical mode decomposition (EMD) method is considered as a major breakthrough in linear and steady-state spectrum analysis based on Fourier transform since 2000. This method decomposes signals according to the time scale characteristics of the data itself, without setting any basis function in advance. This is essentially different from Fourier decomposition and wavelet decomposition based on prior harmonic basis function and wavelet basis function.)

Recent Research in Photovoltaic Industry

Practica 4 par hacer un robot de 4 grados de libertad simulado en Simulink

matlab的FDC工具箱，对飞控系统很有帮助。(matlab the FDC toolbox of helpful flight control system.)

A pv module is modeled in MATLAB/SIMULINK environment with use of mathematical equations that describe pv module s schematic model. This model has 2 inputs named Vpv and insolation and has 2 outputs named Ipv and Ppv. Insolation signal is varying.