this m file can Find a (near) optimal solution to the Traveling Salesman Problem (TSP) by setting up a Genetic Algorithm (GA) to search for the shortest path (least distance needed to travel to each city exactly once) Notes: 1. Input error checking included 2. Inputs can be specified in any order, so long as the Parameter pairs are specified as a Parameter , value
標簽： Traveling Salesman solution Problem
上傳時間： 2013-12-22
上傳用戶：ruixue198909
The source code for this package is located in src/gov/nist/sip/proxy. The proxy is a pure JAIN-SIP application: it does not need proprietary nist-sip classes in addition of those defined in JAIN-SIP 1.1, you can substitute the NIST-SIP stack by another JAIN-SIP-1.1 compliant stack and it should interoperate. he proxy can act as presence server and be able to process NOTIFY and SUBSCRIBE requests. If this Parameter is disabled, the proxy will simply forward those kind of requests following the appropriate routing decision.
標簽： proxy The JAIN-SIP package
上傳時間： 2015-11-30
上傳用戶：ippler8
Carrier-phase synchronization can be approached in a general manner by estimating the multiplicative distortion (MD) to which a baseband received signal in an RF or coherent optical transmission system is subjected. This paper presents a unified modeling and estimation of the MD in finite-alphabet digital communication systems. A simple form of MD is the camer phase exp GO) which has to be estimated and compensated for in a coherent receiver. A more general case with fading must, however, allow for amplitude as well as phase variations of the MD. We assume a state-variable model for the MD and generally obtain a nonlinear estimation problem with additional randomly-varying system Parameters such as received signal power, frequency offset, and Doppler spread. An extended Kalman filter is then applied as a near-optimal solution to the adaptive MD and channel Parameter estimation problem. Examples are given to show the use and some advantages of this scheme.
標簽： synchronization Carrier-phase multiplicativ approached
上傳時間： 2013-11-28
上傳用戶：windwolf2000
The equation is written as a system of two first order ODEs. These are evaluated for different values of the Parameter Mu. For faster integration, we choose an appropriate solver based on the value of the Parameter Mu.
標簽： different evaluated equation written
上傳時間： 2013-12-25
上傳用戶：qazxsw
Comparison of the performances of the LS and the MMSE channel estimators for a 64 sub carrier OFDM system based on the Parameter of Mean square error
標簽： the performances Comparison estimators
上傳時間： 2016-02-01
上傳用戶：hgy9473
This R2.9 revision of the CLID detector provides the TYPE 1 (on-hook, between first and second ring, or before first ring) signal detection and returns the message raw byte data without parsing of particular fields such as Message Type, Parameter(s) Type(s), etc. The decoding of the message meaning should be performed by the user application.主叫號碼識別CID算法for TI DSP
標簽： the revision detector provides
上傳時間： 2014-01-18
上傳用戶：天誠24
NAND Flash Boot Please select function : 0 : USB download file（通過USB下載文件） 1 : Uart download file（通過串口下載文件） 2 : Write Nand flash with download file（將下載的文件燒寫到NandFlash） 3 : Load Pragram from Nand flash and run（從NandFlash裝載文件并運行） 4 : Erase Nand flash regions（擦除NandFlash區域） 5 : Write NOR flash with download file（將下載的文件燒寫到NorFlash） 6 : Set boot params（設置Linux啟動相關參數） 7 : Set AutoBoot Parameter,1:linux 2:wince(設置WINCE自啟動）
標簽： download USB function Please
上傳時間： 2016-02-15
上傳用戶：s363994250
This little Program allows you to send commands to the CardReader (CT-BCS) or to the Card itself. First you will be ask to what Port the Reader is connected (0=COM1, 1=COM2). Then the Class-Byte (CLA), Instruction-Byte (INS), Parameter 1 (P1), Parameter 2 (P2). If wou don愒 want to send Parameter 3 (P3) press Ctrl-d (^d). If you enter a number then you have to the Bytes of the Datafield. After the last Byte of the Datafield is entered the whole APDU is send the replay is displayed. After that you can send the next APDU.
標簽： CardReader the commands to
上傳時間： 2016-04-23
上傳用戶：nanxia
runs Kalman-Bucy filter over observations matrix Z for 1-step prediction onto matrix X (X can = Z) with model order p V = initial covariance of observation sequence noise returns model Parameter estimation sequence A, sequence of predicted outcomes y_pred and error matrix Ey (reshaped) for y and Ea for a along with inovation prob P = P(y_t | D_t-1) = evidence
標簽： matrix observations Kalman-Bucy prediction
上傳時間： 2016-04-28
上傳用戶：huannan88
Kalman filter toolbox written by Kevin Murphy, 1998. See http://www.ai.mit.edu/~murphyk/Software/kalman.html for details. Installation ------------ 1. Install KPMtools from http://www.ai.mit.edu/~murphyk/Software/KPMtools.html 3. Assuming you installed all these files in your matlab directory, In Matlab type addpath matlab/KPMtools addpath matlab/Kalman Demos ----- See tracking_demo.m for a demo of 2D tracking. See learning_demo.m for a demo of Parameter estimation using EM. 較早版本的kalman濾波matlab源碼，適合研讀。
標簽： Software toolbox murphyk written
上傳時間： 2016-05-13
上傳用戶：541657925
