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In this paper, a new family of Cassinian wave-guides
is proposed, simulating and calculation are finished with CST
Microwave Studio that based on Finite Integral Technique (FIT),
and some results are given. Electromagnetic field mode type of it
is TE, electromagnetic field is stronger near neck REGION, and
some resonance frequencies appear. The new Cassinian curve
wave-guides will possess higher power than ones of the
rectangular and elliptic wave-guides because the height at the
position where maximal electric field occurs is smaller.
標(biāo)簽：
calculation
wave-guides
simulating
Cassinian
上傳時(shí)間：
2014-01-18
上傳用戶：netwolf
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我用matlab寫的一個(gè)corner detector, 效果比現(xiàn)在流行的harris，susan，CSS等效果要好。
Algorithm is derived from:
X.C. He and N.H.C. Yung, Curvature Scale Space Corner Detector with Adaptive Threshold and Dynamic REGION of Support , Proceedings of the 17th International Conference on Pattern Recognition, 2:791-794, August 2004.
Improved algorithm has been included in A Corner Detector based on Global and Local Curvature Properties and submitted to Optical Engineering.
標(biāo)簽：
detector
matlab
corner
harris
上傳時(shí)間：
2013-12-30
上傳用戶：569342831
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Summary: Simple face and eye detection
MATLAB Release: R13
Description: You can use this codes for face detection based on color segmentation and eye REGION detection.
標(biāo)簽：
Description
detection
Summary
Release
上傳時(shí)間：
2014-01-03
上傳用戶：xyipie
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-The existence of numerous imaging modalities makes it possible to present different data present in different modalities together thus forming multimodal images. Component images forming multimodal images should be aligned, or registered so that all the data, coming from the different modalities, are displayed in proper locations. Mutual Information is the similarity measure used in this case for optimizing the two images. This method requires estimating joint histogram of the two images. The fusion of images is the process of combining two or more images into a single image retaining important features from each. The Discrete Wavelet Transform (DWT) has become an attractive tool for fusing multimodal images. In this work it has been used to segment the features of the input images to produce a REGION map. Features of each REGION are calculated and a REGION based approach is used to fuse the images in the wavelet domain.
標(biāo)簽：
present
modalities
existence
different
上傳時(shí)間：
2014-03-04
上傳用戶：15736969615
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If you d like to know where visitors to your site live, add this to your feedback forms. They just choose a REGION, and the second menu changes appropriately, allowing them to choose their country. (If they choose USA, it allows them to select their state) Neat!
標(biāo)簽：
your
feedback
to
visitors
上傳時(shí)間：
2017-06-11
上傳用戶：wfeel
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matlab有限元網(wǎng)格劃分程序
DistMesh is a simple MATLAB code for generation of unstructured triangular and tetrahedral meshes. It was developed by Per-Olof Persson (now at UC Berkeley) and Gilbert Strang in the Department of Mathematics at MIT. A detailed description of the program is provided in our SIAM Review paper, see documentation below.
One reason that the code is short and simple is that the geometries are specified by Signed Distance Functions. These give the shortest distance from any point in space to the boundary of the domain. The sign is negative inside the REGION and positive outside. A simple example is the unit circle in 2-D, which has the distance function d=r-1, where r is the distance from the origin. For more complicated geometries the distance function can be computed by interpolation between values on a grid, a common representation for level set methods.
For the actual mesh generation, DistMesh uses the Delaunay triangulation routine in MATLAB and tries to optimize the node locations by a force-based smoothing procedure. The topology is regularly updated by Delaunay. The boundary points are only allowed to move tangentially to the boundary by projections using the distance function. This iterative procedure typically results in very well-shaped meshes.
Our aim with this code is simplicity, so that everyone can understand the code and modify it according to their needs. The code is not entirely robust (that is, it might not terminate and return a well-shaped mesh), and it is relatively slow. However, our current research shows that these issues can be resolved in an optimized C++ code, and we believe our simple MATLAB code is important for demonstration of the underlying principles.
To use the code, simply download it from below and run it from MATLAB. For a quick demonstration, type "meshdemo2d" or "meshdemond". For more details see the documentation.
標(biāo)簽：
matlab有限元網(wǎng)格劃分程序
上傳時(shí)間：
2015-08-12
上傳用戶：凜風(fēng)拂衣袖
-
Abstract—In the future communication applications, users
may obtain their messages that have different importance levels
distributively from several available sources, such as distributed
storage or even devices belonging to other users. This
scenario is the best modeled by the multilevel diversity coding
systems (MDCS). To achieve perfect (information-theoretic)
secrecy against wiretap channels, this paper investigates the
fundamental limits on the secure rate REGION of the asymmetric
MDCS (AMDCS), which include the symmetric case as a special
case. Threshold perfect secrecy is added to the AMDCS model.
The eavesdropper may have access to any one but not more than
one subset of the channels but know nothing about the sources,
as long as the size of the subset is not above the security level.
The question of whether superposition (source separation) coding
is optimal for such an AMDCS with threshold perfect secrecy
is answered. A class of secure AMDCS (S-AMDCS) with an
arbitrary number of encoders is solved, and it is shown that linear
codes are optimal for this class of instances. However, in contrast
with the secure symmetric MDCS, superposition is shown to
be not optimal for S-AMDCS in general. In addition, necessary
conditions on the existence of a secrecy key are determined as a
design guideline.
標(biāo)簽：
Fundamental
Limits
Secure
Class
on
of
上傳時(shí)間：
2020-01-04
上傳用戶：kddlas
-
From the transition of analog to digital communication along with seamless mobility and
high computing power of small handheld devices, the wireless communications industry has
seen tremendous changes leading to the integration of several telecommunication networks,
devices and services over last 30 years. The rate of this progress and growth has increased
particularly in the past decade because people no longer use their devices and networks for
voice only, but demand bundle contents such as data download/streaming, HDTV, HD video ,
3D video conferencing with higher efficiency, seamless connectivity, intelligence, reliability
and better user experience. Although the challenges facing service providers and
telecommunication companies differ by product, REGION, market size, and their areas of
concentration but time to market, efficient utilization of their assets and revenue expansion,
have impacted significantly how to manage and conduct their business while maintaining
sufficient margin.
標(biāo)簽：
Convergence
Networks
Beyond
4G
of
上傳時(shí)間：
2020-05-26
上傳用戶：shancjb
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Optical communication technology has been extensively developed over the
last 50 years, since the proposed idea by Kao and Hockham [1]. However, only
during the last 15 years have the concepts of communication foundation, that
is, the modulation and demodulation techniques, been applied. This is pos-
sible due to processing signals using real and imaginary components in the
baseband in the digital domain. The baseband signals can be recovered from
the optical passband REGION using polarization and phase diversity tech-
niques, as well as technology that was developed in the mid-1980s.
標(biāo)簽：
Transmission
Processing
Digital
Optical
上傳時(shí)間：
2020-05-27
上傳用戶：shancjb
-
In a cellular communication system, a service area or a geographical
REGION is divided into a number of cells, and each cell is served by an
infrastructure element called the base station through a radio interface.
Management of radio interface related resources is a critical design
component in cellular communications.
標(biāo)簽：
Management
Resource
Radio
上傳時(shí)間：
2020-06-01
上傳用戶：shancjb
