RSA,DSA,AES,DES加解密实例

本文介绍了一种满足低功耗u阿婆器的可行方案，带FLASH存储的MCU， 以及数字温度传感器、液晶LCD和一个32KHZ的钟表振荡器。

能够将散乱的点云数据边界点及特征点提取出来，并显示。

偶极子天线、环天线、螺旋天线、切比雪夫天线的方向图仿真MATLAB程序

用帧间差分法和三帧差分法法提取运动目标

FAM和SSCA算法的matlab源程序-detection and identification of signalFAM和SSCA算法的matlab源程序-detection and identification of signalDISCLAIMER NOTICEMTHIS DOCUMENT IS BESTQUALITY AVAILABLE. THECOPY FURNISHED TO DTICCONTAINED A SIGNIFICANTNUMBER OF PAGES WHICH DONOT REPRODUCE LEGIBLY.ilApproved for public release; distribution is unlimitedDETECTION AND IDENTIFICATION OF CYCLOSTATIONARY SIGNALSEvandro luiz da costaLieutenant Commander, brazilian NavyB.S., Instituto Militar de Engenharia, 1980Submitted in partial fulfillmentof the requirements for the degree ofMASTER OF SCIENCE IN ELECTRICAL ENGINEERINGANDMASTER OF SCIENCE IN ENGINEERING ACOUSTICSfrom theNAVAL POSTGRADUATE SCHOOLMarch 1996Author.Evandrodk da costaapproved byRQ求Ralph Hippenstiel, Thesis Co-AdvisorRoberto Cristi, Thesis Ca-AdvisoiHerschel. Loomis, Jr, hairmanDepartment of Electrical and Computer EngineeringArthony A. Atchley / ChairmanEngineering Acoustics Academic CommitteeABSTRACTPropeller noise can be modeled as an amplitude modulated(AM) signalCyclic Spectral Analysis has been used successfully to detect the presence ofanalog and digitally modulated signals in communication systems. It can also identithe type of modulation. Programs for Signal Processing based on compiledlanguages such as FORTRAN or C are not user friendly, and MATLAB basedprograms have become the de facto language and tools for signal processingengineers worldwideThis thesis describes the implementation in mAtlab of two fast methods ofcomputing the Spectral Correlation Density(SCD)Function estimate, the FFTAccumulation Method (FAM)and the Strip Spectral Correlation Algorithm( SSCA),toperform Cyclic Analysis. Both methods are based on the Fast Fourier transformFFT)algorithm. The results are presented and areas of possible enhancement forpropeller noise detection and identification are discussedTABLE OF CONTENTSINTRODUCTIONA MOTIVATION,P,中“····*s···:···:B BACKGROUNDC THESIS GOALSIL NOISE IN THE OCEAN··+A TYPES OF UNDERWATER NOISE25561. Ambient Noise番申2. Self noise3. Radiated noise8B RADIATED NOISE FROM SHIPS, SUBMARINES AND TORPEDOES.......8C PROPELLER NOISE10lI CYCLOSTATIONARY PROCESSING15A CYCLOSTATIONARIT15B THE CYCLIC AUTOCORRELATION FUNCTION (ACF)17C THE SPECTRAL CORRELATION DENSITY FUNCTION (SCD)18N. ESTIMATION OF THE SPECTRAL CORRELATION DENSITY FUNCTION23A FFT ACCUMULATION METHOD(FAM)25B STRIP SPECTRAL CORRELATION ALGORITHM(SSCA■D28V. EXPERIMENTAL RESULTSA. ANALOG-MODULATED SIGNALS311. Amplitude Modulated(AM)Signal===2-312. Pulse-Amplitude Modulated(PAM) Signal58B DIGITAL-MODULATED SIGNALS1. Amplitude Shift Keying(ASK) Signal中中非昏号即即号自唱即自曲音非带卡.最662. Binary-Phase Shift Keying(BPSK) Signal6了VI CONCLUSIONS81A SUMMARY81B SUGGESTIONS82APPENDIX A-CALCULATION OF THE SCD FUNCTION OF AN AMPLITUDE-MODULATED SIGNAL83APPENDIX B-FUNCTION AUTOFAM95APPENDIX C-FUNCTION AUTOSSCA99APPENDIXD-FUNCTION CROSSFAM103APPENDIX E-FUNCTION CROSSSSCA109APPENDIX F-PLOTTING ROUTINES113LIST OF REFERENCES115INITIAL DISTRIBUTION LIST看音117INTRODUCTIONA. MOTIVATIONPropeller related acoustic signatures typically exhibit modulationcharacteristics. These modulation characteristics originate from the cavitationprocess that takes place in the water due to the cyclic movement of the propellerThe cavitation process is basically the collapse of air and vapor bubblesdue to variations in the static pressure. These variations in static pressure are aconsequence of the passage of the propeller blades through the water. Thismovement, cyclic in nature, causes amplitude modulation in the static pressureand as a consequence an amplitude-modulated(AM) signal can be detected in areceiverCyclostationary processing techniques have been used to detect andlentify analog and digital communication signals very successfully. Thesetechniques have the advantage of using a more realistic model for the signalthan the stationary model used in most of the more conventional signalprocessing techniquesB BACKGROUNDThe basic elements of cyclic spectral analysis are the time-variant cyclicperiodogram and the time-variant cyclic correlogram. These two functions form aFourier transform pair. This fact is known as the cyclic Wiener relation or thecyclic Wiener-Khinchin relation [Ref. 1: p. 49.1

图像的隐藏与伪装技术是图像安全方面一个非常重要的研究领域。其中常用的图像置乱算法实现较为复杂,基于Zig-zag变换的思想提出了一种新的数字图像置乱算法,并构造了两个具体的置乱变换方法。通过算法的仿真实验和结果分析表明该算法具有较好的置乱效果及较大的周期,并具有一定的抗攻击能力,从图像信息安全性及算法的时间复杂度方面分析,该算法优于Arnold等变换,将该类算法用于图像加密有一定的应用价值。

这个是自己用Python2.7写的基于opencv的车牌识别,目前识别率还是不怎么高,车牌定位采用的是形态学变换,分割是自己写的一个算法,识别部分采用的是kNN算法,有详细的注释!

【实例简介】SX126x LORA芯片驱动程序，(功能：按键LORA发送任意数据，LORA接收到数据通过串口打印)。附带完整的工程，原理图，数据手册等。工程是基于stm8的，如果要用stm32的话稍微改一下引脚定义和引脚初始化即可。LORA的频率速率等可以根据自己的需求修改，程序里面有备注怎么计算频率

文档中包含一个simulink仿真模型和S函数代码文件，在matlab中设置好路径，就可以成功仿真

串口接收发送数据程序，用485进行接收并发送程序，详细的信息在程序中全部注释好了