PHONETICS , by Irina
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Wednesday, July 18, 2012
Tuesday, February 14, 2012
MATLAB Trainee
Job Description
Need to train the students to the environment of MATLAB, Execution of program, Simulations. Need to co-ordinate lab and class rooms.
Functional Area:Teaching, Education
Role:Trainee
Keyskills:MATLAB Trainee, Trainee, MATLAB, ece, eee, electronics and communiation engineering, electrical engineering, electronics and electrical engineering, lecturer, professor, assistant professor, associate professor, VLSI
Desired Candidate Profile
Education:
(UG - Any Graduate - Any Specialization, B.Tech/B.E. - Electrical, Electronics/Telecomunication) OR
(PG - Any PG Course - Any Specialization, Post Graduation Not Required, M.Tech - Electrical, Electronics/Telecomunication) B.Tech / M.Tech from ECE or EEE department
Read More & Aplly
DSP Professionals_3-8 yrs_Gurgaon
MS/MTech in EE with 3 years of experience or BS/BTech with atleast 5-7 years of experience
Familiarity with Digital Signal Processingconcepts like adaptive filtering and FFTs
Familiarity with Speech compression and Speech Vocoders
Role Category:Programming & Design
Role:Software Developer
Keyskills:dsp digital signal processing
Desired Candidate Profile
Education:(UG - B.Tech/B.E.) OR (PG - M.Tech)
Read More & Apply
Wednesday, February 1, 2012
MATLAB position for Pune Location
Job Description
Role Category:Programming & Design
Role:Team Lead/Technical Lead
Keyskills:matlab, Simulink, Stateflow, Micro controller, C programming, auto - coding, code optimization. RTOS, AUTOSAR
Desired Candidate Profile:
Education:(UG - Any Graduate - Any Specialization, Graduation Not Required, B.Tech/B.E.) AND
(PG - Any PG Course - Any Specialization, Post Graduation Not Required, M.Tech)
Exp: 2 to 4 Yrs
1. B.E./ M.Sc. (Electronics)
2. Automotive domain experience
3. Knowledge on Micro controllers is a must.
4. Should have good knowledge of 'C' programming and Model based (Matlab,Simulink and Stateflow) Development.
5. Experience in auto-coding and code optimization.
6. Good communication skills.
Apply Now
Saturday, November 19, 2011
Overview of the Simulunk Tool
Simulink® software models, simulates, and analyzes dynamic systems. It enables us to pose a question about a system, model the system, and see what happens.
With Simulink, we can easily build models from scratch, or modify existing models to meet your needs. Simulink supports linear and nonlinear systems, modeled in continuous time, sampled time, or a hybrid of the two. Systems can also be multirate — having different parts that are sampled or updated at different rates.
Thousands of scientists and engineers around the world use Simulink to model and solve real problems in a variety of industries, including:
•Aerospace and Defense
•Automotive
•Communications
•Electronics and Signal Processing
•Medical Instrumentation
Tool for Model-Based Design
With Simulink, we can move beyond idealized linear models to explore more realistic nonlinear models, factoring in friction, air resistance, gear slippage, hard stops, and the other things that describe real-world phenomena. Simulink turns our computer into a laboratory for modeling and analyzing systems that would not be possible or practical otherwise.
Whether we are interested in the behavior of an automotive clutch system, the flutter of an airplane wing, or the effect of the monetary supply on the economy, Simulink provides us with the tools to model and simulate almost any real-world problem. Simulink also provides demos that model a wide variety of real-world phenomena.
Simulink provides a graphical user interface (GUI) for building models as block diagrams, allowing us to draw models as we would with pencil and paper. Simulink also includes a comprehensive block library of sinks, sources, linear and nonlinear components, and connectors. If these blocks do not meet our needs, however, we can also create our own blocks. The interactive graphical environment simplifies the modeling process, eliminating the need to formulate differential and difference equations in a language or program.
Models are hierarchical, so we can build models using both top-down and bottom-up approaches. We can view the system at a high level, then double-click blocks to see increasing levels of model detail. This approach provides insight into how a model is organized and how its parts interact.
Tool for Simulation
After we define a model, we can simulate it, using a choice of mathematical integration methods, either from the Simulink menus or by entering commands in the MATLAB® Command Window. The menus are convenient for interactive work, while the command line is useful for running a batch of simulations (for example, if we are doing Monte Carlo simulations or want to apply a parameter across a range of values).
Using scopes and other display blocks, we can see the simulation results while the simulation runs. We can then change many parameters and see what happens for "what if" exploration. The simulation results can be put in the MATLAB workspace for postprocessing and visualization.
Tool for Analysis
Model analysis tools include linearization and trimming tools, which can be accessed from the MATLAB command line, plus the many tools in MATLAB and its application toolboxes. Because MATLAB and Simulink are integrated, we can simulate, analyze, and revise our models in either environment at any point.
How Simulink® Software Interacts with the MATLAB® Environment
Simulink software is tightly integrated with the MATLAB environment. It requires MATLAB to run, depending on it to define and evaluate model and block parameters. Simulink can also utilize many MATLAB features. For example, Simulink can use the MATLAB environment to:
•Define model inputs.
•Store model outputs for analysis and visualization.
•Perform functions within a model, through integrated calls to MATLAB operators and functions.
With Simulink, we can easily build models from scratch, or modify existing models to meet your needs. Simulink supports linear and nonlinear systems, modeled in continuous time, sampled time, or a hybrid of the two. Systems can also be multirate — having different parts that are sampled or updated at different rates.
Thousands of scientists and engineers around the world use Simulink to model and solve real problems in a variety of industries, including:
•Aerospace and Defense
•Automotive
•Communications
•Electronics and Signal Processing
•Medical Instrumentation
Tool for Model-Based Design
With Simulink, we can move beyond idealized linear models to explore more realistic nonlinear models, factoring in friction, air resistance, gear slippage, hard stops, and the other things that describe real-world phenomena. Simulink turns our computer into a laboratory for modeling and analyzing systems that would not be possible or practical otherwise.
Whether we are interested in the behavior of an automotive clutch system, the flutter of an airplane wing, or the effect of the monetary supply on the economy, Simulink provides us with the tools to model and simulate almost any real-world problem. Simulink also provides demos that model a wide variety of real-world phenomena.
Simulink provides a graphical user interface (GUI) for building models as block diagrams, allowing us to draw models as we would with pencil and paper. Simulink also includes a comprehensive block library of sinks, sources, linear and nonlinear components, and connectors. If these blocks do not meet our needs, however, we can also create our own blocks. The interactive graphical environment simplifies the modeling process, eliminating the need to formulate differential and difference equations in a language or program.
Models are hierarchical, so we can build models using both top-down and bottom-up approaches. We can view the system at a high level, then double-click blocks to see increasing levels of model detail. This approach provides insight into how a model is organized and how its parts interact.
Tool for Simulation
After we define a model, we can simulate it, using a choice of mathematical integration methods, either from the Simulink menus or by entering commands in the MATLAB® Command Window. The menus are convenient for interactive work, while the command line is useful for running a batch of simulations (for example, if we are doing Monte Carlo simulations or want to apply a parameter across a range of values).
Using scopes and other display blocks, we can see the simulation results while the simulation runs. We can then change many parameters and see what happens for "what if" exploration. The simulation results can be put in the MATLAB workspace for postprocessing and visualization.
Tool for Analysis
Model analysis tools include linearization and trimming tools, which can be accessed from the MATLAB command line, plus the many tools in MATLAB and its application toolboxes. Because MATLAB and Simulink are integrated, we can simulate, analyze, and revise our models in either environment at any point.
How Simulink® Software Interacts with the MATLAB® Environment
Simulink software is tightly integrated with the MATLAB environment. It requires MATLAB to run, depending on it to define and evaluate model and block parameters. Simulink can also utilize many MATLAB features. For example, Simulink can use the MATLAB environment to:
•Define model inputs.
•Store model outputs for analysis and visualization.
•Perform functions within a model, through integrated calls to MATLAB operators and functions.
Friday, November 18, 2011
Introduction to Simulink® with Engineering Applications
“Introduction to Simulink® with Engineering Applications” is an introduction to Simulink ®, a companion application to MATLAB ®. It is written for students at the undergraduate and graduate programs, as well as for the working professional.
Although some previous knowledge of MATLAB would be helpful, it is not absolutely necessary;
This text is an introduction to MATLAB to enable the reader to begin learning both MATLAB and Simulink simultaneously, and to perform graphical computations and programming.
This book describe the blocks of all Simulink libraries. Their application is illustrated with practical examples through Simulink models, some of which are supplemented with MATLAB functions, commands, and statements. Some background information is provided for lesser known definitions and topics.
Explains the several Simulink models to illustrate various applied math and engineering applications.
Introduces the difference equations as they apply to discrete-time systems, and also introduces the reader to random generation procedures.
Like MATLAB, Simulink can be used with both linear and nonlinear systems, which can be modeled in continuous time, sample time, or a hybrid of these.
Most of the examples presented in this book can be implemented with the Student Versions of MATLAB and Simulink.
Although some previous knowledge of MATLAB would be helpful, it is not absolutely necessary;
This text is an introduction to MATLAB to enable the reader to begin learning both MATLAB and Simulink simultaneously, and to perform graphical computations and programming.
This book describe the blocks of all Simulink libraries. Their application is illustrated with practical examples through Simulink models, some of which are supplemented with MATLAB functions, commands, and statements. Some background information is provided for lesser known definitions and topics.
Explains the several Simulink models to illustrate various applied math and engineering applications.
Introduces the difference equations as they apply to discrete-time systems, and also introduces the reader to random generation procedures.
Like MATLAB, Simulink can be used with both linear and nonlinear systems, which can be modeled in continuous time, sample time, or a hybrid of these.
Most of the examples presented in this book can be implemented with the Student Versions of MATLAB and Simulink.
Download E-Book Here
Sunday, October 16, 2011
Magic Matrix
Input Programme
A=magic(4)
Output result
A =
16 2 3 13
5 11 10 8
9 7 6 12
4 14 15 1
Note: Magic Matrix is a matrix in which the sum of elements of rows, columns and diagonals are equal.
A=magic(4)
Output result
A =
16 2 3 13
5 11 10 8
9 7 6 12
4 14 15 1
Note: Magic Matrix is a matrix in which the sum of elements of rows, columns and diagonals are equal.
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