基于OFDM的無線寬帶系統仿真It contains mainly two parts, i.e. link-level simulator and system-level simulator.
Link-level simulator focus on a single-cell single-user scenario, where signal is transmitted from tx, and estimated at rx. Comparing the difference in tx/rx signal, the error rate can be found out. The output of the link-level simulator is the BLER/BER vs. SNR mapping table, that can be used for the system-level simulation.
System-level simulator focus on a multi-cell multi-user scenario. For the sake of simplicity, it takes the mapping table aquired in the link-level simulation, measure the actural SNR, and finds the corresponding error rate.
三維矢量有限元-矩量法電磁場分析程序。
EMAP5 is a full-wave electromagnetic field solver that combines the method of moments (MOM) with a vector finite element method (VFEM). It employs the finite element method (FEM) to analyze a dielectric volume, and employs the method of moments (MoM) to solve for currents on the surface of (or external to) this volume. The two methods are coupled through the fields on the dielectric surface.
ExcpHook is an open source (see license.txt) Exception Monitor for Windows made by Gynvael Coldwind (of Team Vexillium). t uses a ring0 driver to hook KiExceptionDispatch procedure to detect the exceptions, and then shows information about the exception on stdout (using the ring3 part of the program ofc).
The difference between this method, and the standard debug API method it that this method monitores all of XP processes, and the program does not have to attach to any other process to monitor it, hence it s harder to detect.
The code currently is considered as ALPHA, and it has been reported to BSoD sometimes (on multi core/cpu machines). Take Care!
When working with mathematical simulations or engineering problems, it is not unusual to handle curves that contains thousands of points. Usually, displaying all the points is not useful, a number of them will be rendered on the same pixel since the screen precision is finite. Hence, you use a lot of resource for nothing!
This article presents a fast 2D-line approximation algorithm based on the Douglas-Peucker algorithm (see [1]), well-known in the cartography community. It computes a hull, scaled by a tolerance factor, around the curve by choosing a minimum of key points. This algorithm has several advantages:
這是一個基于Douglas-Peucker算法的二維估值算法。
The MDP toolbox proposes functions related to the resolution of discrete-time Markov Decision Process : finite horizon, value iteration, policy iteration, linear programming algorithms with some variants.
The functions (m-functions) were developped with MATLAB v6.0 (one of the functions requires the Mathworks Optimization Toolbox) by the decision team of the Biometry and Artificial Intelligence Unit of INRA Toulouse (France).
The version 2.0 (February 2005) handles sparse matrices and contains an example
％ EM algorithm for k multidimensional Gaussian mixture estimation
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％ Inputs:
％ X(n,d) - input data, n=number of observations, d=dimension of variable
％ k - maximum number of Gaussian components allowed
％ ltol - percentage of the log likelihood difference between 2 iterations ([] for none)
％ maxiter - maximum number of iteration allowed ([] for none)
％ pflag - 1 for plotting GM for 1D or 2D cases only, 0 otherwise ([] for none)
％ Init - structure of initial W, M, V: Init.W, Init.M, Init.V ([] for none)
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％ Ouputs:
％ W(1,k) - estimated weights of GM
％ M(d,k) - estimated mean vectors of GM
％ V(d,d,k) - estimated covariance matrices of GM
％ L - log likelihood of estimates
％
T-kernel 的extension源代碼，是日本最著名的T-kernel所獨有的，適合開發T-kernel的朋友們使用！
TK/SE is the program that extends T-Kernel and provides the functions such as a file system and a process management.
The TK/SE archive to be provided is comprised of the main portion and the 2 extended file system portions, and TK/SE object is built by adding these to T-Kernel source.
a) tkernel_se_1.00.00.tar.gz Main source of T-Kernel/SE
b) extfs_fatfs_1.00.00.tar.gz Difference source of T-Kernel/SE extended file system (FAT)
c) extfs_cdrom_1.00.00.tar.gz Difference source of T-Kernel/SE extended file system (CD-ROM)
The main features of the considered identification problem are that there is no an a priori separation of the variables into inputs and outputs and the approximation criterion, called misfit, does not depend on the model representation. The misfit is defined as the minimum of the l2-norm between the given time series and a time series that is consistent with the approximate model. The misfit is equal to zero if and only if the model is exact and the smaller the misfit is (by definition) the more accurate the model is. The considered model class consists of all linear time-invariant systems of bounded complexity and the complexity is specified by the number of inputs and the smallest number of lags in a difference equation representation. We present a Matlab function for approximate identification based on misfit minimization. Although the problem formulation is representation independent, we use input/state/output representations of the system in order
A Matlab toolbox for exact linear time-invariant system identification is presented. The emphasis is on the variety of possible ways to implement the mappings from data to parameters of the data generating system. The considered system representations are input/state/output, difference equation, and left matrix fraction.
KEYWORDS: subspace identification, deterministic subspace identification, balanced model reduction, approximate system identification, MPUM.
