Extensively revised for the latest Java (J2SE 5.0) release Deitel Java How to Program, 6/e now includes earlier coverage of objects new and streamlined case studies and OPTIONAL GUI and graphics sections. Now available in a briefer version (ch. 1-10) called Small Java. SafariX version available.
As the Hardware Description Language (HDL) enhancement activities have increased over the past year, so too has the complexity in determining which language(s) are the best tools for designers and organizations to continue using or to adopt. Many designers and organizations are contemplating whether they should switch from one HDL to another.
As the Hardware Description Language (HDL) enhancement activities have increased over the past year, so too has the complexity in determining which language(s) are the best tools for designers and organizations to continue using or to adopt. Many designers and organizations are contemplating whether they should switch from one HDL to another.
The present document specifies the CAMEL Application Part (CAP) supporting the fourth phase of the network feature Customized Applications for Mobile network Enhanced Logic. CAP is based on a sub-set of the ETSI Core INAP CS-2 as specified by ETSI EN 301 140 1 [26]. Descriptions and definitions provided by ETSI EN 301 140 1 [26] are directly referenced by this standard in the case no additions or clarifications are needed for the use in the CAP.
Carrier-phase synchronization can be approached in a
general manner by estimating the multiplicative distortion (MD) to which
a baseband received signal in an RF or coherent optical transmission
system is subjected. This paper presents a unified modeling and
estimation of the MD in finite-alphabet digital communication systems. A
simple form of MD is the camer phase exp GO) which has to be estimated
and compensated for in a coherent receiver. A more general case with
fading must, however, allow for amplitude as well as phase variations of
the MD.
We assume a state-variable model for the MD and generally obtain a
nonlinear estimation problem with additional randomly-varying system
parameters such as received signal power, frequency offset, and Doppler
spread. An extended Kalman filter is then applied as a near-optimal
solution to the adaptive MD and channel parameter estimation problem.
Examples are given to show the use and some advantages of this scheme.
The need for accurate monitoring and analysis of sequential data arises in many scientic, industrial
and nancial problems. Although the Kalman lter is effective in the linear-Gaussian
case, new methods of dealing with sequential data are required with non-standard models.
Recently, there has been renewed interest in simulation-based techniques. The basic idea behind
these techniques is that the current state of knowledge is encapsulated in a representative
sample from the appropriate posterior distribution. As time goes on, the sample evolves and
adapts recursively in accordance with newly acquired data. We give a critical review of recent
developments, by reference to oil well monitoring, ion channel monitoring and tracking
problems, and propose some alternative algorithms that avoid the weaknesses of the current
methods.
We have a group of N items (represented by integers from 1 to N), and we know that there is some total order defined for these items. You may assume that no two elements will be equal (for all a, b: a<b or b<a). However, it is expensive to compare two items. Your task is to make a number of comparisons, and then output the sorted order. The cost of determining if a < b is given by the bth integer of element a of costs (space delimited), which is the same as the ath integer of element b. Naturally, you will be judged on the total cost of the comparisons you make before outputting the sorted order. If your order is incorrect, you will receive a 0. Otherwise, your score will be opt/cost, where opt is the best cost anyone has achieved and cost is the total cost of the comparisons you make (so your score for a test case will be between 0 and 1). Your score for the problem will simply be the sum of your scores for the individual test cases.
This project aims to distribute a facial animation system with speech, developed to brazilian portuguese case. This system is composed by many modules: movement extraction, facial animation and speech, through a text-to-speech system.
TFIND
searches for one or more strings (boolean AND) in a text file.
TFIND reports all lines where the string(s) were found (or NOT found
by option).
The search can be limited to a field in a fixed field (i.e. column
oriented) list.
An extended search mode is available, where only letters and digits
are relevant.
Other options:
case sensitive search,
alternative errorlevel with number of hits,
header line with file name, LFN, custom prefix
