Inverter

阵列信号处理 频率和角度联合估计 JAFE算法(Array signal processing frequency and angle joint estimation algorithm JAFE)

an matlab code for crop face from an frontal and 60 degree image of face. user should select left and right eye respectively first.

小波包分析提取振动信号中的特征频率，语音信号的采集与处理，数字信号处理课设，实现了对10个数字音的识别。( Wavelet packet analysis to extract vibration signal characteristic frequency, Acquisition and Processing of the speech signal, digital signal processing class-based, To achieve the recognition of 10 digital sound.)

新的信号处理方法－希尔伯特黄变换的EMD分解MATLAB程序 把程序看懂 对希尔伯特黄变换的原理就理解了(New signal processing methods- Hilbert Huang Transform EMD decomposition MATLAB program to understand the procedures of the Hilbert Huang transform understanding of the principles on)

混频器建模的Matlab仿真程序！有GUI界面可供进行混频器的参数设置！(Mixer simulation program Matlab modeling! A GUI interface for setting parameters for the mixer!)

脉冲振幅（PAM）的仿真：脉冲振幅调制，即是脉冲载波的幅度随基带信号变化的一种调制方式。如果脉冲载波是由冲激脉冲组成的，则前面所说的抽样定理，就是脉冲振幅调制的原理。(Pulse amplitude (PAM) of the simulation: Pulse amplitude modulation, that is, the range of carrier pulse with changes in base-band signal of a modulation. If the pulse carrier is formed by the impulse of the pulse, then said in front of the sampling theorem, that is, the principle of pulse amplitude modulation.)

code for mppt perturb and observe algorithm

硕士论文，基于机器视觉苹果检测算法的研究。主要内容包括：1、国内外研究现状及进展 2、苹果图像采集与处理 3、苹果大小与形状检测 4、粒子群优化的BP神经网络苹果颜色检测算法 5、遗传算法优化BP神经网络苹果缺陷检测算法 6、苹果检测系统的软件、硬件及界面设计(Research on Apple detection algorithm based on machine vision. The main contents include: 1, the domestic and foreign research present situation and the progress of 2, apple image acquisition and processing 3, the shape and size of Apple detection 4, particle swarm optimization of BP neural network in apple color detection algorithm 5, genetic algorithm optimization BP neural network for Apple defect detection algorithm 6, apple detection system software, hardware and interface design)

Linear discriminant analysis (LDA) and the related Fisher s linear discriminant are methods used in statistics, pattern recognition and machine learning to find a linear combination of features which characterizes or separates two or more classes of objects or events. The resulting combination may be used as a linear classifier, or, more commonly, for dimensionality reduction before later classification.

signal generator matlab simulink