直接传输和远程无线传感器网络中基于路由

Matlab code for fiber bragg gratimg tmm

利用matlab实现语音信号的倒谱分析,通过观察仿真，可以看出倒谱函数的频谱特性。(Matlab voice signal cepstrum analysis, simulation, can be seen by observing the spectral properties of the function cepstrum.)

通过虚拟阵元进行DOA估计，最大信噪比的独立分量分析算法，ldpc码的编解码实现，包含光伏电池模块、MPPT模块、BOOST模块、逆变模块，搭建OFDM通信系统的框架，到达过程是的泊松过程。

丹麦法的matlab算法，没有给出具体数据，适合作为参考程序(Denmark and France s matlab algorithm, did not give specific data, suitable as a reference program)

单脉冲检测的斯威林1和2型曲线 和恒虚警算法检测性能(Single pulse detection Swearingen 1 and type 2 curve ' and CFAR detection algorithm performance)

说明：  基于matlab中的simulink，进行16QAM的仿真搭建。包括了基带信号发生器，串/并模块，模块1，载波调制模块，高斯白噪声信道，模块2，误码率计算器等，能够较好地实现16QAM的调制解调。(Based on the Simulink of MATLAB, the simulation of 16QAM is built. It includes baseband signal generator, serial / parallel module, module 1, carrier modulation module, Gaussian white noise channel, module 2, bit error rate calculator and so on. It can achieve 16QAM modulation and demodulation well.)

on-off keying modulation

说明：  CHAPTER 3 (C3 Folder) BASICS ON MAGNETICS AND LINE MODELING Project 1: Line Parameters and Circuit Models: (a) Relative Accuracy of Circuit Models for Different Line Lengths (b) Real and Reactive Power Transfer SIMULINK file none MATLAB M-file m1.m Project 2: Switching Transients in Single-Phase Line SIMULINK file s2.mdl MATLAB M-file m2.m

已知消息信号为一个长度为8的二进制序列；载波频率为 ，采样频率为4KHz。编程实现一种调制、传输、滤波和解调过程。(Known message signal is a binary sequence with a length of 8 the carrier frequency, the sampling frequency of 4KHz. Programming a modulation, transmission, filtering, and demodulation process.)

本文应用SMQT和 SPLIT UP SNOW 分类器来完成对人脸的检测。(The purpose of this paper is threefold: firstly, the local Successive Mean Quantization Transform features are proposed for illumination and sensor insensitive operation in object recognition. Secondly, a split up Sparse Network of Winnows is presented to speed up the original classifier. Finally, the features and classifier are combined for the task of frontal face detection. Detection results are presented for the MIT+CMU and the BioID databases. With regard to this face detector, the Receiver Operation Characteristics curve for the BioID database yields the best published result. The result for the CMU+MIT database is comparable to state-of-the-art face detectors.)