The C++ Editor is a text editor for C++ programmers. The editor have
color syntax highlighting. Editor s main purpose is to edit source
code files outside the IDE (Integrated Development Environment) with
multiple opened copies of program, when programmer needs to find,
replace or compare source code. The program can compile the file
using for this purpose the Microsoft VC compiler. Most effectively
the editor can be used with a file search utility. The search utility
Search&Edit or IDE Helper is available for download on developer s
WEB site (http://www.easydevtools.com/dwnl_frame.htm).
復接入，B/W雙用戶使用直接擴頻序列
％ >>>multiple access b/w 2 users using DS CDMA
％ >>>format is : cdmamodem(user1,user2,snr_in_dbs)
％ >>>user1 and user2 are vectors and they should be of equal length
％ >>>e.g. user1=[1 0 1 0 1 0 1] , user2=[1 1 0 0 0 1 1],snr_in_dbs=-50
％ >>>or snr_in_dbs=50 just any number wud do
％ Waqas Mansoor
％ NUST , Pakistan
鈥?What Is a Thread?
o The Thread Class
o Simple Thread Examples
鈥?Problems with Multithreading
o What Goes Wrong?
o Thread Names and Current Threads
o Java s synchronized
鈥?Synchronizing Threads
o Multiple Locks
鈥?The Dining Philosophers Problem
o Deadlocks
o A Solution to the Dining Philosophers Problem
o Java s wait() and notify()
o Dining Philosophers Example
鈥?Summary
This project demonstrates the use of secure hash functions technique
to implement a file encryption / decryption system.
This implemented application can encrypt / decrypt multiple files
on the fly using a password. The password supplied by the user
is used as the source message from which the hash code (key) is
generated using the SHA algorithm. Then this key is used to
enctypted the data in the file(s). This key is stored in the
encrypted file along with the encrypted data.
This project demonstrates the use of secure hash functions technique
to implement a file encryption / decryption system.
This implemented application can encrypt / decrypt multiple files
on the fly using a password. The password supplied by the user
is used as the source message from which the hash code (key) is
generated using the SHA algorithm. Then this key is used to
enctypted the data in the file(s). This key is stored in the
encrypted file along with the encrypted data.
In this project we analyze and design the minimum mean-square error (MMSE) multiuser receiver for uniformly quantized synchronous code division multiple access (CDMA) signals in additive white Gaussian noise (AWGN) channels.This project is mainly based on the representation of uniform quantizer by gain plus additive noise model. Based on this model, we derive the weight vector and the output signal-to-interference ratio (SIR) of the MMSE receiver. The effects of quantization on the MMSE receiver performance is characterized in a single parameter named 鈥漞quivalent noise variance鈥? The optimal quantizer stepsize which maximizes the MMSE receiver output SNR is also determined.
3rd Generation Partnership Project
Technical Specification Group Radio Access Network
Spatial channel model for
Multiple Input Multiple Output [MIMO] simulations
The application note covers the various domains of the FIFO
architecture, improving data rate using the multiple buffering
scheme, using the part in port I/O, slave FIFO or the GPIF
c pgm to find redundant paths in a graph.Many fault-tolerant network algorithms rely on an underlying assumption that there are possibly distinct network paths between a source-destination pair. Given a directed graph as input, write a program that uses depth-first search to determine all such paths. Note that, these paths are not vertex-disjoint i.e., the vertices may repeat but they are all edge-disjoint i.e., no two paths have the same edges. The input is the adjacency matrix of a directed acyclic graph and a pair(s) of source and destination vertices and the output should be the number of such disjoint paths and the paths themselves on separate lines. In case of multiple paths the output should be in order of paths with minimum vertices first. In case of tie the vertex number should be taken in consideration for ordering.
Recovering 3-D structure from motion in noisy 2-D images is a problem addressed by many vision system researchers. By consistently tracking feature points of interest across multiple images using a methodology first described by Lucas-Kanade, a 3-D shape of the scene can be reconstructed using these features points using the factorization method developed by Tomasi-Kanade.
