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.
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.
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
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.
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.
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.”
目的:自主研制一款超聲手術刀電源控制系統,以減少能量的消耗,維持手術刀的正常溫度。方法:對超聲換能器在諧振附近的等效電路建立模型,并設計基于數字信號處理(DSP)的超聲手術刀的硬件控制系統。結果:經對電源控制系統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,能夠及時調整電源的頻率,并達到預期的功能指標,使超聲手術刀工作在諧振狀態。結論:以DSP為核心設計的超聲手術刀電源控制系統,測試指標均能夠達到預期的要求,能夠使系統在諧振狀態下工作。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.
應用無跡卡爾曼濾波算法（UKF）進行鋰電池的SOC估計,采用Thevenin二階RC等效電路模型,對HPPC電池脈沖充放電實驗數據進行Matlab處理,得到較為準確的模型.通過在Matlab中編寫算法程序,對不同工況的估計值與實際值進行誤差估算及對比分析,通過此算法進行SOC估計,得到該算法可有效降低系統誤差并糾正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.
