Introduction
Some times it is required that we build a shared library (DLL) from an m-file. M-files are functions that are written in Matlab editor and can be used from Matlab command prompt. In m-files, we employ Matlab built-in functions or toolbox functions to compute something. In my past articles, I showed you some ways to use Matlab engine (vis. API, C++ class or Matlab engine API) for employing Matlab built-in functions, but what about functions that we develop? How can we use them in VC? Is there any interface? This article shows you an idea to employ your own Matlab functions.
How the K-mean Cluster work
Step 1. Begin with a decision the value of k = number of clusters
Step 2. Put any initial partition that classifies the data into k clusters. You may assign the training samples randomly, or systematically as the following:
Take the first k training sample as single-element clusters
Assign each of the remaining (N-k) training sample to the cluster with the nearest centroid. After each assignment, recomputed the centroid of the gaining cluster.
Step 3 . Take each sample in sequence and compute its distance from the centroid of each of the clusters. If a sample is not currently in the cluster with the closest centroid, switch this sample to that cluster and update the centroid of the cluster gaining the new sample and the cluster losing the sample.
Step 4 . Repeat step 3 until convergence is achieved, that is until a pass through the training sample causes no new assignments.
Generate 100 samples of a zero-mean white noise sequence with variance , by using a uniform random number generator.
a compute the autocorrelation of for .
b compute the periodogram estimate and plot it.
c Generate 10 different realizations of , and compute the corresponding sample autocorrelation sequences , and . compute the average autocorrelation sequence as and the corresponding periodogram for .
d compute and plot the average periodogram using the Bartlett method.
e Comment on the results in parts (a) through (d).
DataDraw is an ultra-fast persistent database for high performance programs written in C. It s so fast that
many programs keep all their data in a DataDraw database, even whi le being manipulated in inner loop s
of compute intensive appl ications.
This article introduces how to construct a Hospital Ward Information System with three-tiered technology. The System applies to UML, BDE, MIDAS, distributed compute theory and a special architecture to make such functions: patients check in and check out, prescription input, drug-delivery at center pharmacy and information of patient manage with computer networking.
Process a binary data stream using a communication system that
consists of a baseband modulator, channel, and demodulator.
compute the system s bit error rate (BER). Also, display
the transmitted and received signals in a scatter plot.
It is inserted that the worm will duplicate great.exe to get the systematic materials in the computer of infecting, and produce a script.ini file to reach in mirc catalogue . The worm will utilize emule to disseminate too.
Using an easy-to-follow format, this book explains the basics of MATLAB up front. You ll find out how to plot functions, solve algebraic equations, and compute integrals. You ll also learn how to solve differential equations, generate numerical solutions of ODEs, and work with special functions. Packed with hundreds of sample equations and explained solutions, and featuring end-of-chapter quizzes and a final exam, this book will teach you MATLAB essentials in no time at all.
This is a mutlicore and cluster(of single-core,multi-core systems) matrix inversion code.
Which uses the MPI(Message Passing Interface) for communication across the compute nodes of cluster and using thread-API based OpenMP(Open Multi Processing) between cores of intra-compute or head node.
