perception-algorithm

说明：  这本书是有关精通MATLAB的介绍，有相关例子，值得学习(This book is well versed on the introduction of MATLAB, has relevant examples, it is worth studying)

用MATLAB函数fir1设计一个具有如下指标的线性相位FIR带通滤波器：阻带截止频率为0.55pi 和0.85pi，通带截止频率为0.65pi和 0.75pi，最大通带衰减为0.2dB，最小阻带衰减为42dB。分别利用下面的窗函数来设计滤波器：汉宁窗、汉明窗、布莱克曼窗。对于每种情况，给出其冲激响应系数并画出设计的滤波器的幅频响应。(Designed with a MATLAB function with the following indicators fir1 linear phase FIR band-pass filter: stopband cutoff frequency for the 0.55pi and 0.85pi, passband cutoff frequency of 0.65pi and 0.75pi, maximum passband attenuation is 0.2dB, minimum stopband attenuation of 42dB. Window functions were used to design the following filter: Hanning, Hamming window, Blackman window. For each case, given its impulse response filter coefficients and draw the design magnitude response.)

经典的行人检测算法，利用HOG和SVM实现此算法。已调试可以正常运行。(Classic pedestrian detection algorithm, HOG and SVM to implement this algorithm. Has debugging normal operation.)

有源滤波器的matlab仿真程序，使用了ip-iq电流检测法，中间使用滞环控制产生了控制脉冲，进而实现了谐波电流的补偿，和大家分享了(Active Filter matlab simulation program, using the ip-iq current detection method using hysteresis control generates intermediate control pulse, thus achieving a compensation of harmonic currents, and share the)

无线传感网络DV HOP定位算法仿真 matlab平台源代码(DV HOP wireless sensor network localization algorithm simulation platform source code matlab)

matlab中的A-D检验是一种有效而重要的检验方法，本文介绍了具体的内容及步骤，让大家了解原理。(A-D TEST IS AN IMPORTANT TEST IN MATLAB.)

Channel estimation is detect signal is located in receiver

IIR平滑器的作用和特点演示，包括b取何值时，信号部分通过系统后不变？噪声部分是否放大了？计算NRR和系统频响 (IIR smoother presentation of the role and characteristics, including the b take what value, the signal in part through the system after the change? Whether the part of amplified noise? NRR and system frequency response calculation)

MIT course- Introduction to Matlab

自己调试的GSO程序，简单可运行，适合初学者参考。(The glowworm swarm optimization (GSO) is a swarm intelligence optimization algorithm developed based on the behaviour of glowworms (also known as fireflies or lightning bugs). The behaviour pattern of glowworms which is used for this algorithm is the apparent capability of the glowworms to change the intensity of the luciferin emission and thus appear to glow at different intensities.)