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matlab code for eeg signal generation

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Created at: Monday 03rd of December 2012 11:42:34 PM
Last Edited Or Replied at :Sunday 03rd of February 2013 11:46:33 PM
eeg signal generation , matlab code for eeg signal, help for codes for generation of eeg signal using matlab , matlab code for eeg signal generation, matlab code for eeg signals , seminar for eeg, seminarprojects net matlab code for eeg generation , eeg signals using matlab, matlab coding for eeg signal , coding for eeg signals, signal generation seminar ,

EEG signal g..................[:=> Show Contents <=:]

cognitive radio systems

Posted by: computer science crazy
Created at: Sunday 20th of September 2009 05:35:46 AM
Last Edited Or Replied at :Sunday 20th of March 2011 09:27:11 AM
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ed to substantially suppress these side lobes in order to enable spectrum sharing with primary users. Some of the techniques

been proposed to suppress the side lobe power levels are: windowing the transmitted signal in time domain and/or insertion of

guard bands, singular value decomposition optimization approaches for either inserting cancellation subcarriers or weighting the

subcarriers in order to reduce the side lobe power levels over a neighboring RF spectrum optimization region, transmitting a

modified symbol sequence based on the original sequence but with lower side lobe le..................[:=> Show Contents <=:]

Face Recognition Using Laplacian faces

Posted by: computer science crazy
Created at: Thursday 17th of September 2009 11:45:22 AM
Last Edited Or Replied at :Monday 19th of November 2012 01:44:11 AM
faces , Laplacian, Using , Recognition, Face , laplacian face recognition matlab, matlab codes for face recognition using lpp , image authentication and image processing using independent component anlysis, laplacianfaces , face recognition using lpp,
oad title of factor analysis. The purpose of PCA is to reduce the large dimensionality of the data space (observed variables) to the smaller intrinsic dimensionality of feature space (independent variables), which are needed to describe the data economically. This is the case when there is a strong correlation between observed variables. The jobs which PCA can do are prediction, redundancy removal, feature extraction, data compression, etc. Because PCA is a known powerful technique which can do something in the linear domain, applications having linear models are suitable, such as signal proce..................[:=> Show Contents <=:]


Posted by: Computer Science Clay
Created at: Saturday 13th of June 2009 02:59:30 PM
Last Edited Or Replied at :Saturday 13th of June 2009 02:59:30 PM
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y a few links to others, a handful of
actors, including Rod Steiger and Donald Pleasence, have thousands of
(Incidentally, on a list of most connected actors, Bacon ranked just 876th).
On a more serious note, scale-free networks are present in the biological realm.
With Zoltán Oltvai, a cell biologist from Northwestern
University, we found a scale-free structure in the cellular metabolic networks of
43 different organisms from all three domains of life, including Archaeoglobus
fulgidus (an archaebacterium), Escherichia coli (a eubacterium) and
Caenorhabditis elegan..................[:=> Show Contents <=:]

Impact of Node Mobility on Routing Protocols for Wireless Sensor Networks

Posted by: Computer Science Clay
Created at: Saturday 13th of June 2009 02:19:10 PM
Last Edited Or Replied at :Thursday 04th of March 2010 12:45:28 PM
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s evaluation has been
performed with the aid of various network simulators (such
as ns-2 and others) and synthetic models for mobility and
data patterns. These models can have a great effect upon the
results of the simulation, and thus, the valuation of these
protocols. Some of the models, which are in consideration for
our work, are listed below.
A. Random waypoint (RW) model
The Random Waypoint model is most commonly
used mobility model in research community. This model is
an extension of Random walk. In this model node starts its
journey from a point, chooses a velocity b..................[:=> Show Contents <=:]

image compression

Posted by: Computer Science Clay
Created at: Saturday 06th of June 2009 02:50:26 PM
Last Edited Or Replied at :Thursday 16th of February 2012 12:53:40 AM
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ion lies only in the selection of wavelet filter and the decomposition level. This technique comprises of both the quantization and encoding. As both the processes are carried out in short time the reliability in compressing an image will be high by Fast Image Compression Technique. Since the truncation of the redundant data there is no any notable difference between the original image and synthesized image. This algorithm is not much complex and the memory required to implement the algorithm is not very high. With a strong mathematical background and quantitative analysis, it enables efficien..................[:=> Show Contents <=:]

An Efficient Algorithm for iris pattern Recognition using 2D Gabor Wavelet Trans

Posted by: computer science crazy
Created at: Sunday 21st of September 2008 01:06:40 AM
Last Edited Or Replied at :Saturday 09th of March 2013 05:46:32 AM
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Uniqueness: set by combinatorial complexity.
Patterns apparently stab..................[:=> Show Contents <=:]

A microprocessor-based generator of synchronizing signal and test signal for colour T

Posted by: Electrical Fan
Created at: Sunday 04th of October 2009 04:44:14 AM
Last Edited Or Replied at :Wednesday 07th of November 2012 12:08:19 PM
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ainly based on microprocessor Z-80. Taking the advantage of microprocessor programming, combining with the technique of microprocessor, digital circuits and analogue devices, we use software as far as possible to generate signals directly or to simplify the controlling circuits. Those signals, such as composite sync signal, blanking signal and a series of test signals are originally realized by a number of sequential circuits and logical gates. Now, this test signal generator has smaller size, higher stability and lower cost compared with former ones which consist of more hardware. All of the ..................[:=> Show Contents <=:]

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