JLAB is a set of Matlab functions I have written or co-written over the past fifteen years for the purpose of analyzing data. It consists of four hundred m-files spanning thirty thousand lines of code. JLAB includes functions ranging in complexity from one-line aliases to high-level algorithms for certain specialized tasks. These have been collected together and made publicly available for you to use, modify, and --- subject to certain very reasonable constraints --- to redistribute.
Some of the highlights are: a suite of functions for the rapid Manipulation of multi-component, potentially multi-dimensional datasets a systematic way of dealing with datasets having components of non-uniform length tools for fine-tuning figures using compact, straightforward statements and specialized functions for spectral and time / frequency analysis, including advanced wavelet algorithms developed by myself and collaborators.
With the advent of multimedia, digital signal processing (DSP) of sound has emerged from the shadow of bandwidth-limited speech processing. Today, the main appli- cations of audio DSP are high quality audio coding and the digital generation and Manipulation of music signals. They share common research topics including percep- tual measurement techniques and analysis/synthesis methods. Smaller but nonetheless very important topics are hearing aids using signal processing technology and hardware architectures for digital signal processing of audio. In all these areas the last decade has seen a significant amount of application oriented research.
This is an implementation of double-array structure for representing trie,
as proposed by Junichi Aoe [1].
Trie is a kind of digital search tree, an efficient indexing method with
O(1) time complexity for searching. Comparably as efficient as hashing,
trie also provides flexibility on incremental matching and key spelling
Manipulation. This makes it ideal for lexical analyzers, as well as spelling
dictionaries.
See the details of the implementation at [2]:
http://linux.thai.net/~thep/datrie/datrie.html
Historically, this was first implemented as C++ classes in a library called
midatrie [2], but later simplified and rewritten from scratch in C.
Objectives
The purpose of this notebook is to give you a brief introduction to the
DiscreteWavelets Toolbox and show you how to use it to load
images. Some basic image Manipulation is illustrated as well. You will
also learn how to use measures and tools such as cumulative energy,
entropy, PSNR, and Huffman coding.
Help on the DiscreteWavelets Toolbox
Help for the toolbox is available by clicking on Help and then Product
Help (or press F1) and then clicking on the DiscreteWavelets Toolbox.
Several demos and examples are available as well by clicking on the Demos
tab on the Help menu.
Image Basics
The DiscreteWavelets Toolbox comes with 18 grayscale images and 9 color
images for you to use. There are three functions available to tell you more about these images.
The first function is called |ImageList|. This function can tell you the
names and sizes of the digital images in the Toolbox.
Parallel robotic manipulators can be considered a well-established option
for many different applications of Manipulation, machining, guiding,
testing, control, tracking, haptic force feed-back, etc. A typical parallel robotic
manipulator (PM) consists of a mobile platform connected to the
base (fixed platform) by at least two kinematic chains called limbs. The
mobile platform can achieve between one and three independent translations
(T) and one to three independent rotations (R).
The primary goal of MySQL and Java Developer’s Guide is to provide a comprehensive
approach to writing code from a Java application to a MySQL database
using the industry standard: JDBC. As you will see later in this
Introduction, the chapter titles indicate what area of database connectivity and
Manipulation they cover. The chapters are ordered to reflect the JDBC specification,
but we aren’t here to simply describe the specification.
Matlab 畫三維立體圖形
The aim of geom3d library is to handle and visualize 3D geometric primitives
such as points, lines, planes, polyhedra... It provides low-level functions
for manipulating 3D geometric primitives, making easier the development of more
complex geometric algorithms.
Some features of the library are:
- creation of various shapes (3D points, 3D lines, planes, polyhedra...)
through an intuitive syntax.
Ex: createPlane(p1, p2, p3) to create a plane through 3 points.
- derivation of new shapes: intersection between 2 planes, intersection between
a plane and a line, between a sphere and a line...
- functions for 3D polygons and polyhedra. Polyhedra use classical vertex-faces
arrays (face array contain indices of vertices), and support faces with any
number of vertices. Some basic models are provided (createOctaedron,
createCubeoctaedron...), as well as some computation (like faceNormal or
centroid)
- Manipulation of planar transformation. Ex.:
ROT = createRotationOx(THETA);
P2 = transformPoint3d(P1, ROT);
- direct drawing of shapes with specialized functions. Clipping is performed
automatically for infinite shapes such as lines or rays. Ex:
drawPoint3d([50 50 25; 20 70 10], 'ro'); % draw some points
drawLine3d([X0 Y0 Z0 DX DY DZ]); % clip and draw straight line
Some functions require the geom2d package.
Additional help is provided in geom3d/Contents.m file, as well as summary files
like 'points3d.m' or 'lines3d.m'.
