mani: MANIfold learning demonstration GUI by Todd Wittman, Department of Mathematics, University of Minnesota E-mail wittman@math.umn.edu with comments & questions.
MANI Website: httP://www.math.umn.edu/~wittman/mani/index.html
Last Modified by GUIDE v2.5 10-Apr-2005 13:28:36
Methods obtained from various authors.
(1) MDS -- Michael Lee
(2) ISOMAP -- J. Tenenbaum, de Silva, & Langford
(3) LLE -- Sam Roweis & Lawrence Saul
(4) Hessian LLE -- D. Donoho & C. Grimes
(5) Laplacian -- M. Belkin & P. Niyogi
(6) Diffusion Map -- R. Coifman & S. Lafon
(7) LTSA -- Zhenyue Zhang & Hongyuan Zha
Semantic analysis of multimedia content is an on going research
area that has gained a lot of attention over the last few years.
Additionally, machine learning techniques are widely used for multimedia
analysis with great success. This work presents a combined approach
to semantic adaptation of neural network classifiers in multimedia framework.
It is based on a fuzzy reasoning engine which is able to evaluate
the outputs and the confidence levels of the neural network classifier, using
a knowledge base. Improved image segmentation results are obtained,
which are used for adaptation of the network classifier, further increasing
its ability to provide accurate classification of the specific content.
PRINCIPLE: The UVE algorithm detects and eliminates from a PLS model (including from 1 to A components) those variables that do not carry any relevant information to model Y. The criterion used to trace the un-informative variables is the reliability of the regression coefficients: c_j=mean(b_j)/std(b_j), obtained by jackknifing. The cutoff level, below which c_j is considered to be too small, indicating that the variable j should be removed, is estimated using a matrix of random variables.The predictive power of PLS models built on the retained variables only is evaluated over all 1-a dimensions =(yielding RMSECVnew).
In computer vision, sets of data acquired by sampling the same scene or object at different times, or from different perspectives, will be in different coordinate systems. Image registration is the process of transforming the different sets of data into one coordinate system. Registration is necessary in order to be able to compare or integrate the data obtained from different measurements. Image registration is the process of transforming the different sets of data into one coordinate system. To be precise it involves finding transformations that relate spatial information conveyed in one image to that in another or in physical space. Image registration is performed on a series of at least two images, where one of these images is the reference image to which all the others will be registered. The other images are referred to as target images.
OTSU Gray-level image segmentation using Otsu s method.
Iseg = OTSU(I,n) computes a segmented image (Iseg) containing n classes
by means of Otsu s n-thresholding method (Otsu N, A Threshold Selection
Method from Gray-Level Histograms, IEEE Trans. Syst. Man Cybern.
9:62-66 1979). Thresholds are computed to maximize a separability
criterion of the resultant classes in gray levels.
OTSU(I) is equivalent to OTSU(I,2). By default, n=2 and the
corresponding Iseg is therefore a binary image. The pixel values for
Iseg are [0 1] if n=2, [0 0.5 1] if n=3, [0 0.333 0.666 1] if n=4, ...
[Iseg,sep] = OTSU(I,n) returns the value (sep) of the separability
criterion within the range [0 1]. Zero is obtained only with images
having less than n gray level, whereas one (optimal value) is obtained
only with n-valued images.
this program solves the steady-state navier-stokes eqn in 2d for the flow in a driven cavity problem.
the function solved for is the streamfunction.
the velocity may be obtained by differentiating
the streamfunction.
The MINI2440 is an effecient ARM9 development board with a comprehensive price, it characterizes simple method and high performance-price ratio. Based on the Samsung S3C2440 microprocessor, it embodies professional stable CPU core power source chip and reset chip to ensure the stability of the system operation. The PCB on the MINI2440 board is designed to be 4-layers board, adopting the ENIG technology and professional equal-length wiring to ensure the completeness of the signals of the key signal wires and manufactured and released under stringent quality control plans. With the help of this detailed manual, users are supposed to become proficient in the development process of embedded Linux and WinCE operating system, they are supposed to get the foundation, so long as they have obtained the basic and necessary knowledge about the C language, in two weeks.
This books presents the research work of COST 273 Towards Mobile Broadband Multimedia
Networks, hence, it reports on the work performed and on the results achieved within the project
by its participants. The material presented here corresponds to the results obtained in four years
of collaborative work by more than 350 researchers from 137 institutions (universities, operators,
manufacturers, regulators, independent laboratories and others – a full list is provided in Appendix
B) belonging to 29 countries (mainly European, but also from Asia and North America) in the area of
mobileradio. Theobjectiveofpublishingtheseresultsasabookisessentiallytomakethemavailable
to an audience wider than the project. In fact, it just follows a ‘tradition’ of previous COST Actions
in this area of telecommunications, i.e. COST 207, 231 and 259.
Rapid growth of wireless communication services in recent decades has created
a huge demand of radio spectrum. Spectrum scarcity and utilization inefficiency
limit the development of wireless networks. Cognitive radio is a promising tech-
nology that allows secondary users to reuse the underutilized licensed spectrum of
primary users. The major challenge for spectrum sharing is to achieve high spectrum
efficiency while making non-intrusive access to the licensed bands. This requires in-
formation of availability and quality of channel resources at secondary transmitters,
however, is difficult to be obtained perfectly in practice.
The first gem of wisdom I ever acquired about consulting, obtained many years ago
from a former schoolmate, was to ensure that everything is plugged in: no continuity, no
data. Wires carry voltages and currents from one place to another. Their behavior is
reasonably simple and predictable—at least for sufficiently low data rates and short
lengths—and they can be seen, grabbed, traced, and tugged.