The purpose of this chapter is to present a survey of Recent publications concerning medical
image registration techniques. These publications will be classified according to a model based
on nine salient criteria, the main dichotomy of which is extrinsic versus intrinsic methods
In Recent years large scientific interest has been
devoted to joint data decoding and parameter estimation
techniques. In this paper, iterative turbo decoding joint
to channel frequency and phase estimation is proposed.
The phase and frequency estimator is embedded into the
structure of the turbo decoder itself, taking into consideration
both turbo interleaving and puncturing. Results
show that the proposed technique outperforms conventional
approaches both in terms of detection capabilities and
implementation complexity.
Core JSP
In Recent years, a large amount of software development activity has migrated from
the client to the server. The client-centric model, in which a client executes complex
programs to visualize and manipulate data, is no longer considered appropriate for the
majority of enterprise applications. The principal reason is deployment—it is a
significant hassle to deploy client programs onto a large number of desktops, and to
redeploy them whenever the application changes. Instead, applications are redesigned
to use a web browser as a "terminal". The application itself resides on the server,
formatting data for the user as web pages and processing the responses that the user fills into web forms.
In Recent years, the UNIX operating system has seen a huge boost in its popularity, especially with the
emergence of Linux. For programmers and users of UNIX, this comes as no surprise: UNIX was designed to
provide an environment that s powerful yet easy to use.
One of the main strengths of UNIX is that it comes with a large collection of standard programs. These
programs perform a wide variety of tasks from listing your files to reading email. Unlike other operating
systems, one of the key features of UNIX is that these programs can be combined to perform complicated
tasks and solve your problems.
One of the most powerful standard programs available in UNIX is the shell. The shell is a program that
provides you with a consistent and easy-to-use environment for executing programs in UNIX. If you have
ever used a UNIX system, you have interacted with the shell.
模式識別學(xué)習(xí)綜述.該論文的英文參考文獻為303篇.很有可讀價值.Abstract— Classical and Recent results in statistical pattern
recognition and learning theory are reviewed in a two-class
pattern classification setting. This basic model best illustrates
intuition and analysis techniques while still containing the essential
features and serving as a prototype for many applications.
Topics discussed include nearest neighbor, kernel, and histogram
methods, Vapnik–Chervonenkis theory, and neural networks. The
presentation and the large (thogh nonexhaustive) list of references
is geared to provide a useful overview of this field for both
specialists and nonspecialists.
Recent work by Petricoin and Liotta and co-workers (Petricoin et al. Use of proteomic patterns in serum to identify ovarian cancer. Lancet. 2002 Feb 16 359(9306):572-7. PMID: 11867112) has generated a lot of excitement and controversy. This example shows some ways that MATLAB can be used to read, visualize, pre-process (base-line correction, resample) and classify the data. The data can be downloaded from
http://home.ccr.cancer.gov/ncifdaproteomics/ppatterns.asp
Sequential Monte Carlo without Likelihoods
粒子濾波不用似然函數(shù)的情況下
本文摘要:Recent new methods in Bayesian simulation have provided ways of evaluating posterior distributions
in the presence of analytically or computationally intractable likelihood functions.
Despite representing a substantial methodological advance, existing methods based on rejection
sampling or Markov chain Monte Carlo can be highly inefficient, and accordingly
require far more iterations than may be practical to implement. Here we propose a sequential
Monte Carlo sampler that convincingly overcomes these inefficiencies. We demonstrate
its implementation through an epidemiological study of the transmission rate of tuberculosis.
Recent advances in experimental methods have resulted in the generation
of enormous volumes of data across the life sciences. Hence clustering and
classification techniques that were once predominantly the domain of ecologists
are now being used more widely. This book provides an overview of these
important data analysis methods, from long-established statistical methods
to more Recent machine learning techniques. It aims to provide a framework
that will enable the reader to recognise the assumptions and constraints that
are implicit in all such techniques. Important generic issues are discussed first
and then the major families of algorithms are described. Throughout the focus
is on explanation and understanding and readers are directed to other resources
that provide additional mathematical rigour when it is required. Examples
taken from across the whole of biology, including bioinformatics, are provided
throughout the book to illustrate the key concepts and each technique’s
potential.
