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  • SA Encryption and Decryption using Matlab The program set contains thirteen files listed below.

    SA Encryption and Decryption using Matlab The program set contains thirteen files listed below. errormeg.fig errormsg.m helpmsg.fig helpmsg.m inputmsg.fig inputmsg.m mesgcut.m pro2.fig pro2.m rsacore.m readme.txt screenshot.gif In order to run the program please call pro2.m under Matlab 6.0 Environment. System Requirement Matlab version 6.0 and if necessary, Maple version 6.0 on any platform PentiumII 300 MHz or equivalent.

    標(biāo)簽: Encryption Decryption contains thirteen

    上傳時(shí)間: 2017-04-06

    上傳用戶:dreamboy36

  • OTSU Gray-level image segmentation using Otsu s method. Iseg = OTSU(I,n) computes a segmented i

    OTSU Gray-level image segmentation using Otsu s method. Iseg = OTSU(I,n) computes a segmented image (Iseg) containing n classes by means of Otsu s n-thresholding method (Otsu N, A Threshold Selection Method from Gray-Level Histograms, IEEE Trans. Syst. Man Cybern. 9:62-66 1979). Thresholds are computed to maximize a separability criterion of the resultant classes in gray levels. OTSU(I) is equivalent to OTSU(I,2). By default, n=2 and the corresponding Iseg is therefore a binary image. The pixel values for Iseg are [0 1] if n=2, [0 0.5 1] if n=3, [0 0.333 0.666 1] if n=4, ... [Iseg,sep] = OTSU(I,n) returns the value (sep) of the separability criterion within the range [0 1]. Zero is obtained only with images having less than n gray level, whereas one (optimal value) is obtained only with n-valued images.

    標(biāo)簽: OTSU segmentation Gray-level segmented

    上傳時(shí)間: 2017-04-24

    上傳用戶:yuzsu

  • The code for this article was written for version 1.0 of the Active Template Library (ATL). The cu

    The code for this article was written for version 1.0 of the Active Template Library (ATL). The current version of the code (in SieveATL) was built with Visual C++ 6.0 and the ATL provided with that compiler. It may be slightly different than the code shown in the article. The directory SieveMFC contains an MFC version of a component equivalent to the ATL version discussed in the article. It was built with version 5 of the C++ compiler and the MFC version provided with it. The code discussed in the article was later adapted for Hardcore Visual Basic, Second Edition. Comparable Visual Basic versions are discussed in Chapter 10 of the book. Bruce McKinney

    標(biāo)簽: The for Template Library

    上傳時(shí)間: 2013-12-01

    上傳用戶:古谷仁美

  • Pascal 7 to Delphi 2005 code conversion or update to replace pascal unit files Graphics, Keyboard,

    Pascal 7 to Delphi 2005 code conversion or update to replace pascal unit files Graphics, Keyboard, Mouse commands to equivalent in Delphi 2005

    標(biāo)簽: conversion Graphics Keyboard replace

    上傳時(shí)間: 2014-01-21

    上傳用戶:zjf3110

  • Like many of my colleagues in this industry, I learned Windows programming from Charles Petzold s Pr

    Like many of my colleagues in this industry, I learned Windows programming from Charles Petzold s Programming Windows—a classic programming text that is the bible to an entire generation of Windows programmers. When I set out to become an MFC programmer in 1994, I went shopping for an MFC equivalent to Programming Windows. After searching in vain for such a book and spending a year learning MFC the old-fashioned way, I decided to write one myself. It s the book you hold in your hands. And it s the book I would like to have had when I was learning to program Windows the MFC way.

    標(biāo)簽: programming colleagues industry Charles

    上傳時(shí)間: 2014-01-10

    上傳用戶:曹云鵬

  • conversion From 32-bit Hexadecimal Representation To Decimal Floating-Point Along with the Equival

    conversion From 32-bit Hexadecimal Representation To Decimal Floating-Point Along with the equivalent 64-bit Hexadecimal and Binary Patterns

    標(biāo)簽: Floating-Point Representation Hexadecimal conversion

    上傳時(shí)間: 2017-09-27

    上傳用戶:yimoney

  • 基于頻率插值的4.0kbps 語音編碼器的性能和設(shè)計(jì)(英文)

    The 4.0 kbit/s speech codec described in this paper is based on a Frequency Domain Interpolative (FDI) coding technique, which belongs to the class of prototype waveform Interpolation (PWI) coding techniques. The codec also has an integrated voice activity detector (VAD) and a noise reduction capability. The input signal is subjected to LPC analysis and the prediction residual is separated into a slowly evolving waveform (SEW) and a rapidly evolving waveform (REW) components. The SEW magnitude component is quantized using a hierarchical predictive vector quantization approach. The REW magnitude is quantized using a gain and a sub-band based shape. SEW and REW phases are derived at the decoder using a phase model, based on a transmitted measure of voice periodicity. The spectral (LSP) parameters are quantized using a combination of scalar and vector quantizers. The 4.0 kbits/s coder has an algorithmic delay of 60 ms and an estimated floating point complexity of 21.5 MIPS. The performance of this coder has been evaluated using in-house MOS tests under various conditions such as background noise. channel errors, self-tandem. and DTX mode of operation, and has been shown to be statistically equivalent to ITU-T (3.729 8 kbps codec across all conditions tested.

    標(biāo)簽: frequency-domain interpolation performance Design kbit_s speech coder based and of

    上傳時(shí)間: 2018-04-08

    上傳用戶:kilohorse

  • Cognitive+Networked+Sensing+and+Big+Data

    The idea of writing this book entitled “Cognitive Networked Sensing and Big Data” started with the plan to write a briefing book on wireless distributed computing and cognitive sensing. During our research on large-scale cognitive radio network (and its experimental testbed), we realized that big data played a central role. As a result, the book project reflects this paradigm shift. In the context, sensing roughly is equivalent to “measurement.”

    標(biāo)簽: Cognitive Networked Sensing Data Big and

    上傳時(shí)間: 2020-05-26

    上傳用戶:shancjb

  • 基于數(shù)字信號處理的超聲手術(shù)刀電源控制電路設(shè)計(jì)與實(shí)現(xiàn)

    目的:自主研制一款超聲手術(shù)刀電源控制系統(tǒng),以減少能量的消耗,維持手術(shù)刀的正常溫度。方法:對超聲換能器在諧振附近的等效電路建立模型,并設(shè)計(jì)基于數(shù)字信號處理(DSP)的超聲手術(shù)刀的硬件控制系統(tǒng)。結(jié)果:經(jīng)對電源控制系統(tǒng)的電路和工作性能測試,生成的電流和電壓的有效值等參數(shù),能夠及時(shí)調(diào)整電源的頻率,并達(dá)到預(yù)期的功能指標(biāo),使超聲手術(shù)刀工作在諧振狀態(tài)。結(jié)論:以DSP為核心設(shè)計(jì)的超聲手術(shù)刀電源控制系統(tǒng),測試指標(biāo)均能夠達(dá)到預(yù)期的要求,能夠使系統(tǒng)在諧振狀態(tài)下工作。Objective: To independently develop a power control system of ultrasonic scalpel so as to reduce the energy consumption and maintain the normal temperature of ultrasonic scalpel. Methods: In this paper, the model of equivalent circuit of ultrasonic transducer nearby syntony was built up, and the hardware control system of ultrasonic scalpel based on digital signal processing(DSP) was designed. Results: Through testing the circuit and work performance of power control system, the series of parameters such as effective value and so on which were produced by this system could adjust frequency of power source in time and attain anticipative functional indicator, and it took the ultrasonic scalpel to work in syntonic situation. Conclusion: The tested indicators of power control system of ultrasonic scalpel based on the kernel design of DSP can attain anticipative requirement, and can take this system to work in syntonic situation.

    標(biāo)簽: 數(shù)字信號處理 超聲手術(shù)刀 電源控制

    上傳時(shí)間: 2022-04-03

    上傳用戶:bluedrops

  • 基于無跡卡爾曼濾波算法的鋰電池SOC估計(jì)

    應(yīng)用無跡卡爾曼濾波算法(UKF)進(jìn)行鋰電池的SOC估計(jì),采用Thevenin二階RC等效電路模型,對HPPC電池脈沖充放電實(shí)驗(yàn)數(shù)據(jù)進(jìn)行Matlab處理,得到較為準(zhǔn)確的模型.通過在Matlab中編寫算法程序,對不同工況的估計(jì)值與實(shí)際值進(jìn)行誤差估算及對比分析,通過此算法進(jìn)行SOC估計(jì),得到該算法可有效降低系統(tǒng)誤差并糾正SOC的初值偏差.The non trace Calman filter (UKF) is applied to the SOC estimation of lithium battery. The Thevenin two order RC equivalent circuit model is used to process the HPPC battery pulse charge discharge experimental data by Matlab processing, and a more accurate model is obtained. By writing algorithm program in Matlab, the error estimation and comparison analysis of the estimated value and actual value of different states are carried out, and the SOC estimation is carried out by this algorithm. The algorithm can effectively reduce the system error and correct the initial value deviation of the SOC.

    標(biāo)簽: 卡爾曼濾波

    上傳時(shí)間: 2022-05-03

    上傳用戶:默默

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