For the incomplete methods, we kept the representation Of the queens by a table and the method Of calculation to determine if two queens are in conflict, which is much faster for this kind Of problems than the representation by a matrix.
heuristics: descent.
Tests: 100 queens in less than 1 second and 67 iterations. 500 queens in 1 second and 257 iterations. 1000 queens in 11 seconds and 492 iterations.
heuristics: Simulated annealing.
Tests: 100 queens in less than 1 second and 47 iterations. 500 queens in 5 seconds and 243 iterations. 1000 queens in 13 seconds and 497 iterations.
heuristics: based on Simulated Annealing.
Tests: 100 queens in less than 1 second and 60 iterations. 500 queens in 1 second and 224 iterations. 1000 queens in 5 seconds and 459 iterations. 10 000 queens in 20 minutes 30 seconds and 4885 iterations.
The subject which is to us propos¨¦ is as follows: calculation Of the degr¨¦ d¡ ¯ inconsistance d¡ ¯ un logical program possibilist in C++. We thus work on a logical program possibilist, it be-¨¤-statement a logical program resulting from non-classique logic. The goal first Of this project is Of d¨¦ terminer if a logical program is consisting or not Of share the calculation Of sound degr¨¦ d¡ ¯ inconsistance.
The program SPLAY is a pascal to C translation Of a program that
Kim Kokkonen wrote in Turbo Pascal to implement Splay Trees.
This program compresses and decompresses files, and does a pretty good
job Of it.
Contents:
SPLAY.PAS Original TP source code
SPLAY.C Translation Of code to C
SPLAY.EXE Compiled version Of SPLAY.C (small model)
README.DOC You are looking at it
Read the comments at the beginning Of SPLAY.C for more info.
to show the waveform Of audio file and play it on computer
Purpose: Familiar with WAV file format and UI design
It should have the following functions:
Provide a Graphic User Interface for user to browse the file system and select one WAV file
Show the waveform Of input audio signal
Play the selected WAV file
Print the parameters Of WAV file such as sampling rate, bit-depth, etc
The adaptive Neural Network Library is a collection Of blocks that implement several Adaptive Neural Networks featuring
different adaptation algorithms.~..~
There are 11 blocks that implement basically these 5 kinds Of neural networks:
1) Adaptive Linear Network (ADALINE)
2) Multilayer Layer Perceptron with Extended Backpropagation algorithm (EBPA)
3) Radial Basis Functions (RBF) Networks
4) RBF Networks with Extended Minimal Resource Allocating algorithm (EMRAN)
5) RBF and Piecewise Linear Networks with Dynamic Cell Structure (DCS) algorithm
A simulink example regarding the approximation Of a scalar nonlinear function Of 4 variables is included
This m file models a DPSK UWB system using a delay in one leg Of the mixer, correlation receiver low pass filter combination requiring no template for synching. Various waveforms are displayed throughout the system to allow the user to observe operation Of the system.
