Using Jacobi method and Gauss-Seidel iterative methods to solve the following system
The required precision is =0.00001, and the maximum iteration number N=25. Compare the number of iterations and the convergence of these two methods
μC/OS-II Goals
Probably the most important goal of μC/OS-II was to make it backward compatible with μC/OS (at least from an
application’s standpoint). A μC/OS port might need to be modified to work with μC/OS-II but at least, the application
code should require only minor changes (if any). Als ...
//
// Histogram Sample
// This sample shows how to use the Sample Grabber filter for video image processing.
// Conceptual background:
// A histogram is just a frequency count of every pixel value in the image.
// There are various well-known mathematical operations that you can perform on an image ...
Matlab is an ideal tool for simulating digital communications systems, thanks to
its easy scripting language and excellent data visualization capabilities. One of the
most frequent simulation tasks in the field of digital communications is bit-error-
rate testing of modems. The bit-error-rate perfor ...
SimpliciTI™ -1.0.3.exe for CC11xx and CC25xx
SimpliciTI is a simple low-power RF network protocol aimed at small (<256) RF networks. Such networks typically contain battery operated devices which require long battery life, low data rate and low duty cycle and have a limited number of nodes talk ...
SimpliciTI™ -1.0.4.exe for CC2430
SimpliciTI is a simple low-power RF network protocol aimed at small (<256) RF networks. Such networks typically contain battery operated devices which require long battery life, low data rate and low duty cycle and have a limited number of nodes talking direct ...
Sequential Monte Carlo without Likelihoods
粒子滤波不用似然函数的情况下
本文摘要:Recent new methods in Bayesian simulation have provided ways of evaluating posterior distributions
in the presence of analytically or computationally intractable likelihood functions.
Despite representing a substantial ...
The last step in training phase is refinement of the clusters
found above. Although DynamicClustering counters all the
basic k-means disadvantages, setting the intra-cluster similarity
r may require experimentation. Also, a cluster may
have a lot in common with another, i.e., sequences assigned
to i ...
