First of all we would like to thank God Almighty for giving us the strength and confidence in
pursing the ambitions. We would like to thank our Examiner Professor Axel Jantsch for
allowing us to do this under his guidance and encouragement. At the same time we would like
to mention our sincere thanks to Mr. Said Zainali, Manager of FRAME ACCESS AB for
giving all the required equipment and the technical support which helped us to finish this
thesis. We would like to mention our gratitude to our fellow VACS team members who helped
us a lot during difficult times.
A series of .c and .m files which allow one to perform univariate and bivariate wavelet analysis of discrete time series. Noother wavelet package is necessary -- everything is contained in this archive. The C-code computes the DWT and maximal overlap DWT. MATLAB routines are then used to compute such quantities as the wavelet variance, covariance, correlation, cross-covariance and cross-correlation. Approximate confidence intervals are available for all quantities except the cross-covariance and cross-correlation.
A set of commands is provided. For a description of this example, please see http://www.eurandom.tue.nl/whitcher/software/.
C# BigInteger class. BigInteger.cs is a csharp program. It is the BIgInteger class. It has methods: abs() , FermatLittleTest(int confidence) ,gcd(BigInteger bi) , genCoPrime(int bits, Random rand) , genPseudoPrime(int bits, int confidence, Random rand) , genRandomBits(int bits, Random rand) , isProbablePrime(int confidence) , isProbablePrime() , Jacobi(BigInteger a, BigInteger b) , LucasSequence(BigInteger P, BigInteger Q, BigInteger k, BigInteger n) ,max(BigInteger bi) , min(BigInteger bi) , modInverse(BigInteger modulus) , RabinMillerTest(int confidence) ,
Testbenches have become an integral part of the design process, enabling you to verify that your HDL model is sufficiently tested before implementing your design and helping you automate the design verification process. It is essential, therefore, that you have confidence your testbench is thoroughly exercising your design. Collecting code coverage statistics during simulation helps to ensure the quality and thoroughness of your tests.
Testbenches have become an integral part of the design process, enabling you to verify that
your HDL model is sufficiently tested before implementing your design and helping you automate
the design verification process. It is essential, therefore, that you have confidence your
testbench is thoroughly exercising your design. Collecting code coverage statistics during simulation
helps to ensure the quality and thoroughness of your tests.
Finally: a hands-on, Java-centric workbook companion for the classic Design Patterns! Workbook approach deepens your understanding, builds your confidence, and strengthens your skills. Covers all five categories of design pattern intent: interfaces, responsibility, construction, operations, and extensions. CD-ROM contains all code examples from the book -- plus bonus code examples not found in the book. About the Author: Steven John Metsker is a researcher and author focused on advanced techniques for magnifying the abilities of object-oriented software developers. A rising star in the patterns community, he was recently invited to join the acclaimed Hillside Group. He is author of Building Parsers with Java? (Addison-Wesley).
an approach for capturing similarity between words that was concerned with the syntactic similarity of two strings. Today we are back to discuss another approach that is more concerned with the meaning of words. Semantic similarity is a confidence score that reflects the semantic relation between the meanings of two sentences. It is difficult to gain a high accuracy score because the exact semantic meanings are completely understood only in a particular context.
