The first objective of Kalman filtering With a radar tracking implementation is to give deep enough insight into the mathematics of the Kalman filter algorithm to be able to choose the correct type of algorithm and to set all the parameters correctly in a basic application. This description also includes several examples of different approaches to derive and to explain the Kalman filter algorithm.
Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Low-Cost Super-Resolution Algorithms Implementation over a HW/SW Video Compression Platform
We also present a variant of the algorithm that performs modular multiplication by interleaving the shift-and-add and the modular reduction steps. The modular multiplication algorithm can be used to obtain eﬃcient VLSI implementations of exponentiation cryptosystems.
C# programmers: no more translating data structures from C++ or Java to
use in your programs! Mike McMillan provides a tutorial on how to use data
structures and algorithms plus the first comprehensive reference for C# implementation
of data structures and algorithms found in the .NET Framework
library, as well as those developed by the programmer.
This book is to examine the most important algorithms in use on
today's computers and to teach the basic techniques with the increasing number
who was interested in computer users becoming increasingly serious. It is appropriate
for use as a textbook for a course Monday, Tuesday or Wednesday in the computer
Science: After students have had some programming skills and familiarity
computer system, but before they have advanced specialized courses
field of computer science or computer applications.
This is the first Visual Basic.NET (VB.NET) book to provide a comprehensive
discussion of the major data structures and algorithms. Here, instead of having
to translate material on C++ or Java, the professional or student VB.NET
programmer will find a tutorial on how to use data structures and algorithms
and a reference for implementation using VB.NET for data structures and
algorithms from the .NET Framework Class Library as well as those that
must be developed by the programmer.
This book is intended to survey the most important algorithms in use on
computers today and to teach fundamental techniques to the growing number
of people who are interested in becoming serious computer users. It is appropriate
for use as a textbook for a second, third or fourth course in computer
science: after students have acquired some programming skills and familiarity
with computer systems, but before they have specialized courses in advanced
areas of computer science or computer applications.
Algorithm is used to define the notion of decidability. It is a set of rules that precisely
defines a sequence of operations. This is essential for computers to process
information. Computer programs contain algorithms that detail specific instructions
a computer should perform to carry out a specified task. The traditional computer
program performs specific instructions sequentially, and uses crisp values of
information which do not support uncertainties.
A filter is a system that is designed to alter the spectral content of input signals in a specified manner. Common filtering objectives include improving signal quality, extracting information from signals, or separating signal components that have been previously combined. A digital filter is a mathematical algorithm implemented in hardware, firmware, and/or software that operates on a digital input signal to produce a digital output signal for achieving filtering objectives.
Ho Chi Minh City University of Technology Faculty of Computer Science and Engineering
Data Structures and Algorithms – C++ Implementation
Huỳnh T n t
Email: email@example.com Home Page: http://www.cse.hcmut.edu.vn/~htdat/
.Pointer in C++
Declaration Node *ptr; Create an object ptr = new Node(); A pointer usage printf(“Data in node: %d”, ptr-data); Destroy an object delete ptr; NULL pointer ptr = NULL;
Faculty of Computer Science and Engineering – HCMUT Slide 2
It’s convenient to describe a data structure in terms of the operations performed, rather than in terms of implementation details.
That means we should separate the concepts from particular implementations.
When a data structure is defined that way, it’s called an abstract data type (ADT).
This book offers a concise introduction to the art of building simulation software, collecting the most important concepts and algorithms in one place. Written for both individuals new to the field of modeling and simulation as well as experienced practitioners, this guide explains the design and implementation of simulation software used in the engineering of large systems while presenting the relevant mathematical elements, concept discussions, and code development.
This book is intended to survey the most important algorithms in use on computers today and to teach fundamental techniques to the growing number of people who are interested in becoming serious computer users. It is appropriate
for use as a textbook for a second, third or fourth course in computer science: after students have acquired some programming skills and familiarity with computer systems, but before they have specialized courses in advanced
areas of computer science or computer applications.
My first contact with speech coding was in 1993 when I was a Field Application
Engineer at Texas Instruments, Inc. Soon after joining the company I was assigned
to design a demo prototype for the digital telephone answering device project.
Initially I was in charge of hardware including circuit design and printed circuit
board layout. The core of the board consisted of a microcontroller sending
commands to a mixed signal processor, where all the signal processing tasks—
including speech coding—were performed.
Any message written over a fixed set of symbols can be represented as a binary string (a sequence of 0's and 1's)
Binary digits 0 and 1 are called bits
To reduce computation overhead, encryption algorithms should only use operations that are easy to implement
For a binary string X:
The length of X, denoted by |X|, is the number of bits in X
If |X| = l, X is an l-bit binary string
Let a be a binary bit and k a non-negative integer. Denote by ak a binary string consisting of k copies of a
Denote the concatenation of X and Y by XY or...
In this paper, we report our parallel implementations of the Lanczos sparse linear system solving algorithm over large prime ﬁelds, on a multi-core platform. We employ several load-balancing methods suited to these platforms.
Parallel Implementation of MAFFT on CUDA-Enabled Graphics Hardware present a new approach to accelerat- ing MAFFT on Graphics Processing Units (GPUs) using the Compute Uniﬁed Device Architecture (CUDA) programming model. Compared with the implementations of other MSA algorithms on GPUs, parallelization of MAFFT is more challenging since the space complexity.
This paper proposes a new probabilistic algorithm for solving multi-objective optimization problems - Probability-Driven Search Algorithm. The algorithm uses probabilities to control the process in search of Pareto optimal solutions. Especially, we use the absorbing Markov Chain to argue the convergence of the algorithm. Authors test this approach by implementing the algorithm on some benchmark multi-objective optimization problems, and find very good and stable results.
Distribution Management (DM), formerly known as Velocity Management (VM), is an Army initiative to dramatically improve the performance of key logistics processes: distribution, repair, stockage determination, and financial management. This monograph describes how the then Velocity Management initiative was used to develop and implement a new algorithm for computing inventories maintained by Army supply support activities (SSAs). The new algorithm is called dollar cost banding (DCB), and it departs in important ways from the methodology that the Army had been using.
The algorithm is implemented on top of the Selective Gain Computation (SGC) algorithm (Zhou et al., 2003), which offers fast training and high quality models. Theoretically, the new algorithm is able to explore an unlimited amount of features. Because of the improved capability of the CME algorithm, we are able to consider many new features and feature combinations during model construction.