Topics Practices:
Programming and Numerical Methods
Practice 1: Introduction to C
Practice 2: Cycles and functions
First part cycles
Part Two: Roles
Practice 3 - Floating point arithmetic
Practice 4 - Search for roots of functions
Practice 5 - Numerical Integration
Practice 6 - Arrangements and matrices
Part One: Arrangements
Part II: Matrices
Practice 7 - Systems of linear equations
Practice 8 - Interpolation
Practice 9 - Algorithm Design techniques
PseudoQ is an open source java application for creating, playing and solving SuDoku puzzles of various types. It features both a Swing GUI and command-line operation. The automatic solving of puzzles uses "smart" techniques rather than a brute force search of every possible combination.
Beginning with tips for the person who is programming with SQL for the first time, SQL Tips and techniques grows with your skills. You can start with Tip 1, "Understanding the Definition of a Database," and by the last Tip, "Displaying Image Data Stored Within a SQL Table," you will have covered all aspects of SQL.
C programming is a craft that takes years to perfect. A reasonably sharp person can learn the basics of
C quite quickly. But it takes much longer to master the nuances of the language and to write enough
programs, and enough different programs, to become an expert. In natural language terms, this is the
difference between being able to order a cup of coffee in Paris, and (on the Metro) being able to tell anative Parisienne where to get off. This book is an advanced text on the ANSI C programming
language. It is intended for people who are already writing C programs, and who want to quickly pick
up some of the insights and techniques of experts.
GRE 數(shù)學(xué)圣經(jīng)，下面是詳細(xì)的英文介紹：
Comprehensive Prep for GRE Math
Every year, students pay $1,000 and more to test prep companies to prepare for the math section of the GRE. Now you can get the same preparation in a book.
Although the GRE math section is difficult, it is very learnable. GRE Math Bible presents a thorough analysis of GRE math and introduces numerous analytic techniques that will help you immensely, not only on the GRE but in graduate school as well.
This report presents a tutorial of fundamental array processing and beamforming theory relevant to microphone array speech processing. A microphone array consists of multiple microphones placed at different spatial locations. Built upon a knowledge of sound propagation principles, the multiple inputs can be manipulated to enhance or attenuate signals emanating from particular directions. In this way, microphone arrays provide a means of enhancing a desired signal in the presence of corrupting noise sources. Moreover, this enhancement is based purely on knowledge of the source location, and so microphone array techniques are applicable to a wide variety of noise types. Microphone arrays have great potential in practical applications of speech processing, due to their ability to provide both noise robustness and hands-free signal acquisition.
To locate the theory of Lie groups within mathematics, one can say that Lie
groups are groups with some additional structure that permits us to apply
analytic techniques such as differentiation in a group theoretic context.
The 4.0 kbit/s speech codec described in this paper is based on a
Frequency Domain Interpolative (FDI) coding technique, which
belongs to the class of prototype waveform Interpolation (PWI)
coding techniques. The codec also has an integrated voice
activity detector (VAD) and a noise reduction capability. The
input signal is subjected to LPC analysis and the prediction
residual is separated into a slowly evolving waveform (SEW) and
a rapidly evolving waveform (REW) components. The SEW
magnitude component is quantized using a hierarchical
predictive vector quantization approach. The REW magnitude is
quantized using a gain and a sub-band based shape. SEW and
REW phases are derived at the decoder using a phase model,
based on a transmitted measure of voice periodicity. The spectral
(LSP) parameters are quantized using a combination of scalar
and vector quantizers. The 4.0 kbits/s coder has an algorithmic
delay of 60 ms and an estimated floating point complexity of
21.5 MIPS. The performance of this coder has been evaluated
using in-house MOS tests under various conditions such as
background noise. channel errors, self-tandem. and DTX mode
of operation, and has been shown to be statistically equivalent to
ITU-T (3.729 8 kbps codec across all conditions tested.
