Thursday, 20 October 2016

Feedback Control Design Assignment help


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  • Motivation, differential equations, complex variables,  matrix methods, Block diagrams, dynamic systems, Linearization of nonlinear equations, State-space description, Response of dynamic systems: transfer functions, pole and zero, locations on dynamic behavior, Stability, More effects of feedback, Frequency response of open loop systems, Designing feedback compensation using frequency response, Root locus technique.
  •  ziegler-nichols tuning, feedforward block diagrams, Feedback control, dynamic models, Laplace, LTI properties, In state variable form, Linearization, Pole-zero locations & time response, Stability, routh criteria, Root loci examples, Dynamic compensation,  bode plots, Nyquist stability criterion, Stability margins, Lead-lag compensation
  • State space: analysis & equations, transfer function, Controllability, observability, State feedback, Pole placement, Observer design, Linear quadratic regulator, Discrete time control, Control systems, Modeling, Laplace transforms, Modeling of op-amps and electric motors, State space representation, Transfer functions and block diagram algebra, Time response, Rise time, settle time, overshoot,  Steady state error.
  • Design via root locus, Frequency response techniques, Bode plots, Design via frequency response, Difference equations and the z-transform, Discrete-time controller design, Modeling dynamic systems, Laplace transforms and solving for system response , Transfer functions, Poles and zeros and system response, Final Value Theorem, Block diagrams, Response to sinusoidal inputs, Closed-loop system, Performance criteria, System type tracking errors disturbance rejection
  • The Routh array PID control, controllers from a root locus perspective, compensators, Lead lag and notch compensators, Frequency domain analysis and Bode plots , Frequency domain analysis and controller synthesis, Nyquist stability
    Design engineering, Spacetechnology, Shape, MIMO, Uncertainty, Stabilization, Design Constraints, Loopshaping, Advanced Loopshaping, Model Matching, Design for Performance, Flexible Beam, Norm Minimization, Stability Margin Optimization, Optimal Robust Stability, Conformal Mapping Gain Margin Optimization, Phase Margin Optimization, Spectral Factorization

Low Dimensional Modeling Assignment help


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Development and analysis of such models for problems arising in neuroscience and, as time permits, fluid dynamics mathematical modeling and analysis techniques which can be applied to problems from engineering, physics, chemistry, and biology.
  • Neuroscience Modeling
  • conductance-based neuron models, such as the Hodgkin-Huxley equations
  • simple reductions of conductance-based neuron models
  • nullcline analysis of neuron models
  • integrate-and-fire neuron models
  • phase response curves and isochrons for periodically firing neurons
  • dynamics of coupled neurons
  • reduction of coupled neuron systems to phase models
  • analysis of phase-locked solutions for coupled neuron systems
  • analysis of bursting neuron models
  • Fluid Dynamics Modeling
  • basics of fluid dynamics
  • derivation of low-dimensional models using Galerkin projection
  • analysis of the Lorenz equations for fluid convection, a prototypical chaotic system
  • analysis of a model for shear flow turbulence derived using Galerkin projection
  • basics of center manifold reduction
  • derivation of low-dimensional models using symmetry methods
  • analysis of a model for binary fluid convection derived using symmetry methods
  • derivation of low-dimensional models using the proper orthogonal decomposition
  • analysis of a model for shear flow turbulence derived using the proper orthogonal decomposition
  • pseudospectra analysis of linear models for shear flow turbulence
  •  Classifier Type: Decision Trees, Discriminant Analysis, Logistic Regression, SVM Support Vector Machines, Nearest Neighbor, Ensembles

Matlab HDL Code Generation and Verification Assignment help


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Topics for HDL Code Generation and verification  
  • Preparing Simulink Models for HDL Code Generation, Generating: HDL code & test bench, generated HDL code with an HDL simulator, Interfacing external HDL code, Interfacing vendor party IP.
  • Preparing a multirate model for generating HDL code, Generating HDL code with single clock pins, multiple clock pins, speed optimizations, area optimizations, hardware description languages, VHDL fundamentals.
  • behavioral model, structural models, syntax , basic rules, design entry, behavioral simulation, logic synthesis , synthesizeable code development, design mapping to standard cells , field programmable gate array.
  •  FPGA or ASIC implementation, Perform design iterations, target-independent VHDL or Verilog code for FPGAs and ASICs.
  • Generating HDL code and testbench for a compatible Simulink model, Performing speed and area optimizations, Integrating handwritten code and existing IP, Verifying generated HDL code using testbench and cosimulation and HDL simulator, Synthesizing the generated HDL code using a HDL synthesis tool, Documenting and Tracing HDL Code, HDL Coding Standard.

Desktop and Web Deployment using Matlab Assignment Help


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MATLAB based programs can be deployed as standalone applications, add-ins for Microsoft Excel, and software components that can be integrated into web and enterprise applications. You can deploy any MATLAB program covering a range of industries and applications such as data analytics, semiconductor/electronics, manufacturing systems, image processing, aerospace/defense, and financial services.
All applications and components are encrypted to protect your intellectual property and can be shared royalty free.When compared with manually recoding algorithms, deploying your MATLAB applications and components provides advantages, such as:
  • Domain experts can maintain ownership of ideas, algorithms, and applications.
  • Software developers have the flexibility to integrate a common algorithm with different programming languages and platforms.
  • Organizations gain efficiency by avoiding time consuming and error prone recoding, as well as easily adopting algorithm improvements throughout the application’s lifecycle.

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Matlab provides integrated capabilities for the exploration of algorithm design and for the effective deployment of the embedded software and desktop. The environment of the matlab helps to explore the multiple approaches and ideas. 
The high level language automatically maintain the low level language like Matlab. Matlab enables to edit, debug and test different kind of design without linking or compiling. It customize the rich set of algorithms and functions which is already implemented in matlab language. Matlab consist of various tools for the effective algorithm design including:
MATLAB Editor: - It provides the features of editing and debugging like stepping by the individual line of code, setting break points
MATLAB Profiler: - It measures the performance of the program and identifies that areas which needs to be modify for the improvement.
Code Analyzer: - It automatically checks the problems in the code and immediately recommend the modification to maximize the performance.
Command Window: - It is basically used to enter data, manipulating command, programs and display results.
Additional tools: Besides it there are some additional tool which is used to compare the data files. After comparing the data files and code it provides the report showing dependencies of the file, code coverage, and annotated reminders.

Mathematical Modeling using Matlab Assignment help


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Online Mathematical Modeling using Matlab Assignment help with topics like Linear Programming, Nonlinear Programming, Difference Equations, Simulation Modeling, One Variable Optimization, Sensitivity Analysis, Multivariable Optimization, Constraint Optimization.
Computational Methods for Optimization, Linear Programming -, Simplex Method, Dynamic Models, Continuous Time Dynamical Models, Discrete Time Dynamical Systems are considered very complex & an expert help is required in order to solve the assignments based on topics like Stability of Equilibria. Phase Portraits, Control Theory, Pontryagin, Maximum Principle, Pontryagin Maximum Principle, Simulation of Dynamic Models, Euler Method, Chaotic Behavior in Nonlinear Systems.
Building models, Flow diagrams, mathematical equations, Testing models, Studying models, black box or white box models, groups of variables: decision variables, input variables, state variables, exogenous variables, random variables, and output variables, dynamical systems, statistical models, differential equations, or game theoretic models.
Technology and mathematics: document creation (LaTeX), computer algebra software (Maxima), spreadsheet programming, and wiki authoring, Difference equations, Applications of linear algebra, Stochastic processes, Data analysis, abstract theory and applications, Geometry of hypersurfaces, Large time behaviour for diffusive Hamilton, area-preserving crystalline curvature flow equation

Stochastic Performance Modeling Assignment help


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Stochastic Performance Modeling
  • Open/closed queueing networks
  • Operational laws
  • M/M/1 queue Burke’s theorem and reversibility
  • M/M/k queue
  • M/G/1 queue
  • G/M/1 queue
  • P h/P h/k queues and their solution using matrix-analytic methods
  • Arrival theorem and Mean Value Analysis
  • Analysis of scheduling policies (e.g., Last-Come-First Served; Processor Sharing)
  • Jackson network and the BCMP theorem (product form networks)
  • Asymptotic analysis (M/M/k queue in heavy/light traf- fic, Supermarket model in mean-field regime)

Embedded Code Generation in Matlab Assignments Help


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  • Design real-time applications 
  • Generate C and C++ code from MATLAB
  • Optimize code for specific processor architectures
  • Integrate generated code with hand-written software 
  • verify embedded code on microcontrollers and DSPs
  • Address industry certification standards
  • support for AUTOSAR and ASAP2
  • traceability reports
  • code interface documentation
  • MATLAB operators, functions and system objects
  • validate MATLAB algorithms compliant
  • Handle typical design patterns

Matlab Rapid Prototyping Assignments Help


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MATLAB RAPID PROTOTYPING INCLUDES:
fast and inexpensive way for control and signal processing , verify designs early ,design tradeoffs ,Test new system designs ,algorithms on hardware in real time, design iterations , Embedded Control Systems , Signal Processing and Imaging Systems,hardware-in-the-loop testing.
Tune model parameters , apply numerical optimization , and run what-if scenarios for controller bandwidth , floating-point vs. fixed-point robustness , and other design considerations , Compare multiple control designs on different boards , analyze design and cost trade-offs.

Data Acquisition using Matlab Assignment Help


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Online Data Acquisition using Matlab Assignment help tutors help with topics like Making Quality Measurements, Accuracy and Precision, Noise, Matching the Sensor Range and A/D Converter Range, Data Acquisition Toolbox, Intended Audience, Triggers, State Transitions, The Data Block, The Data Acquisition Session, Initialization, Configuration, Execution, Termination Related Products, Requirements.
Data Acquisition MATLAB :
  • Sensors , transducers, signal conditioning, dynamic range, calibration, bandwidth, processor throughput, sample rate , aliasing, principles of analogue to digital , principles of digital to analogue converters.
  • ADC specifications, resolution, accuracy, linearity, offset , quantization errors, time-based measurements , jitter, microprocessor interfacing, serial interfaces, multi-channel ADC’s, internal microcontroller ADC’s, Codecs, line drivers , receivers, high power output drivers , high power output devices, LabVIEW Programming.
  • Programming Structures, Autoindexing, Structure, Creating Subvi's Debugging, Timing issues , Global variables, local variables, Arrays, Clusters, File read/write, graph, Embedded Script with Matlab, GPIB, RS232, USB communication, Socket programmingData acquisition board.

Mechatronics using Matlab Assignments Help


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Online Mechatronics using Matlab Assignment help experts with years of experience in the academic field as a professor are helping students online at Undergraduate , graduate & the research level .Our tutors are providing online assistance related to various topics like Powerful code, Speed, Pointers, Graph objects, Two-layer implementation of the database.
Generally topics like The bondgraph ob ject, The databases pool and db, DESIGNER'S VIEW ON THE INTERFACE are considered very complex & an expert help is required in order to solve the assignments based on topics like The User Interface, Automatic Model Transformations.
Topics:
  • mechanical, electrical, control, and embedded software subsystems integration
  • Model based design
  • Simscape electronics
  • Modeling mechatronic systems in Simulink
  • Real time testing and embedded softwaredevelopment
  • CAD designs import
  • Numerical optimization for parameter estimation
  • Linear and non-linear control design
  • PLC implementation

Matlab Programming Assignment help

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Topics for Advanced Matlab Assignment help :
  • Graphics , matlab UI , Pre-defined dialogs , Graphics objects , matlab Menu-driven programs ,Controls: uimenu and uicontrol , Interactive graphics , Large program logic flow  ,Digital Image Processing ,Face recognition ,Iris recognition ,Finger Print recognition ,Fusion Technique , Optic Disk Segmentation ,Palm Print recognition ,Image Fusion ,Voice recognition ,WIRELESS NETWORK ,Cognitive Radio (Spectrum Sensing) ,Spectrum Sensing ,VANET ,MANET
  • WSN (Wireless Sensor Network) ,Zegbee ,network security ,Water Marking ,Cryptograph ,Number Plate Recognition, Emission Load Dispatch, Image Compression , Graphical programming ,Simple graphics , 2D plots , Figures and subplots ,function plotting , lint code checker,precedence and dispatching,matlab tools,Data and data flow in Matlab , Data types , Matrix, string, cell and structure , Data analysis ,Algorithms ,RTFM, JFGI ,Control other applications , non-native data , Remote-controlling/distributed computing, Mixed text-binary files , Communication with external devices , 
  • Serial port ,Parallel port , Polynomial fit, 1D and 2D fits,Sound card, Video input  , matlab questions , exercise problems , exams & technical paper writing
  • Communications in Simulink ,CAN Database ,Curve Fitting using Matlab ,Datafeed using Matlab , matlab DSP Systems , Filter Design, HDL Coder  , Finance using Matlab ,Gauges ,Matlab Coder , Matlab Distributed Computing Server .Advanced Matlab syntax , Building Reusable Graphical Classes , ODE solver suite in Matlab , Simulink architecture and programming , CMEX interface , Java and Java classes in Matlab , XML in Matlab , 
  • CMEX Application Programmer Interface ,mexFunction gateway, mx and mex APIs ,Medical Imaging , Security ,System & Cybernetics , Artificial neural network ,Energy , Filters & denosing , Genetic algorithms , Geo Science , Networking , Stenography , Watermarking , Artificial networks , Communication systems , Power electronics ,Wireless & Remote sensing.

Wednesday, 19 October 2016

Matlab Projects & Assignment Help

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MATLAB stands for matrix laboratory and it is a numerical computing environment. MATLAB is a high-level language and have interactive environment for numerical computation, visualization, and programming. With the help of MATLAB one can analyze data, develop algorithms, and create models and applications. It has tools, and many built-in math functions which help in reaching a solution faster than with spreadsheets or with other traditional programming languages such as C/C++ or Java.

MATLAB allows- Matrix manipulations

Plotting of functions and data

Implementation of algorithms, creation of user interfaces

Interfacing with programs that are written in other programming languages such as C,C++,Java and Fortran.

MATLAB is widely used in academic and research institutions as well as in industrial enterprises.

 Features of Matlab are-

Matlab is a high-level language for numerical computation, visualization, and application development. It provides an interactive environment for iterative exploration, design, and problem solving. Matlab provides mathematical functions for linear algebra, statistics, Fourier analysis, filtering, optimization, numerical integration, and for solving ordinary differential equations.

It has many built-in graphics for visualizing the data and has many tools for creating custom plots. It provides development tools for improving the quality of code and maintainability and maximizing its performance. Matlab have tools for building applications with custom graphical interfaces.

Some of the applications of MATLAB are-Signal processing and communications, Image and video processing,Control systems,Test and measurement,Computational finance,Computational biology. matrix functions: A’ – transpose of matrix A. det(A) – determinant of A eig(A) – Eigen values and Eigen vectors

inv(A) – inverse of A svd(A) – singular value decomposition norm(A) – matrix or vector norm find(A) – find indices of elements that are nonzero.   A few useful math functions: sqrt(x) – square root sin(x) – sine function. exp(x) – exponential log(x) – natural log log10(x) – common log abs(x) – absolute value mod(x) – modulus

Controls Assignment help


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Controls
  • Analysis, design, and evaluation of linear control systems
  • Derive the models for basic physical systems
  • Analyze the steady-state and transient behavior of basic feedback systems
  • Determine stability and performance of feedback systems using time-domain and
  • frequency domain analysis methods
  • Design lead-lag controllers to achieve design specifications
  • Perform basic simulation to verify system stability and performance
  • Stability of linear time invariant systems  
  • Root Locus techniques  
  • Stability in the frequency domain  
  • Design of control systems  
  • Design of state variable feedback systems  
  • Robust control  
  • Digital control
  • current interest in controls 

Discrete-Event Simulation using Matlab Assignments Help


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Discrete-Event Simulation using Matlab:
Discrete -event simulation with SimEvents  gives abilities to investigating and streamlining occasion driven correspondence utilizing cross breed framework models, specialists based models, state graphs, and procedure streams. 
SimEvents programming consolidates discrete-occasion framework displaying into the Simulink time-based structure, which is suited for demonstrating consistent time and intermittent discrete-time frameworks. In time-based frameworks, state transitions happen synchronously with time. 
By complexity, in discrete-occasion frameworks, state moves rely on upon asynchronous discrete occurrences called events.The framework is a basic lining framework in which "clients" — elements — arrive at an altered deterministic rate, hold up in a line, and development to a server that works at a settled deterministic rate.
 This sort of framework is known as a D/D/1 lining framework in lining documentation. The documentation demonstrates a deterministic arrival rate, a deterministic administration rate, and a solitary server. 

Physical Modeling using Matlab Assignment help


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Online Physical Modeling using Matlab Assignment help experts with years of experience in the academic field as a professor are helping students online at Undergraduate , graduate & the research level .
Our tutors are providing online assistance related to various topics like Assignment and equality, Incremental development, Unit testing, Loops, Updating variables, Kinds of error, Absolute and relative error, for loops, plotting, Sequences, Series.
Generalization, Vectors, Checking preconditions, Relational operators, Logical operators, Vectors, Vector arithmetic, Indices, Indexing errors, Vectors and sequences, Plotting vectors are considered very complex. 
An expert help is required in order to solve the assignments based on topics like Reduce, Apply, Search, Spoiling the fun, Name Collisions, Functions, Documentation, Function names, Multiple input variables, Logical functions, Nested loops, Conditions and flags.

Simulink for System and Algorithm Modeling Assignments Help


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Our tutors are providing online assistance related to various topics like Modeling Continuous Systems, throttle system, model for  throttle system, continuous states, Run simulations and analyze results, Model impact dynamics.
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 The formatting of digital video is confusing as the video files include two different elements known as the codec and the container and codec is used inside the container.Mpeg-4 give description of both container and a codec therefore from context it is not always clear. A codec is an algorithm which is compressed and it is utilized to decrease the stream size. 
Therefore it is meant that a mathematical process of decreasing the size of file by taking parts and by not including the other parts of the data. There are codecs which are dependent on audio as well as video like MPEG-1, MPEG-2, MPEG-4.For video related data the word file format is used to determine the format of container. 
The format related to container is used to determine the file layout and a codec do decryption and encryption. Various formats of container can utilized encoded data with various codecs. For reading a file related to video an application should-
-determine the format of container like AVI 
-Have codec access which can decode the data of video stored inside a file. Few codecs are standard 
Windows part and part of Macintosh related system and allow to play inside in quick time and Windows Media Player.

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MATLAB Fundamentals:
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  • Helps and demos, Relationship with Excel, Programming language, Basic symbols and commands, Mathematical functions and operators table, Logical operators, Functions created by the user, MATLAB graphics, Using toolboxes, MATLAB.
  • The most useful command in MATLAB, The heart of MATLAB: matrices, Creating Matrices, Transposing and concatenating matrices, Indexing, Assignment and deletion, Reshaping and Replication, Matrix manipulations, Sparse Matrices, Flow of Control, Scripts and functions, Creating functions, Functions: other issues, 1D/2D plots, 3D plots, Customise plots.

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MATLAB clients can influence NVIDIA GPUs to quicken computationally concentrated applications in areas, for example, picture preparing, sign handling, and computational fund. Compting incorporates GPU-empowered usefulness in MATLAB and different extra tool compartments, and  integration of custom CUDA bits into MATLAB. It incorporates how MATLAB supports CUDA kernel improvement by giving a high level language and advancement environment for prototyping calculations and incrementally creating and testing CUDA kernels.  
Information must be sent from the CPU to the GPU before estimation and retrieve later. Since a GPU is connected to the host CPU through the PCI Express transport, the memory access is slower than with a conventional CPU.
This implies that  general computational speedup is constrained by the measure of information transfer that takes place in  algorithm.Using MATLAB for GPU figuring permits to quicken the applications with GPUs more effectively than by utilizing C or Fortran. With the well known MATLAB dialect an  advantage can be taken of the CUDA GPU computing innovation without having to learn the intricacies of GPU architectures or low-level GPU figuring libraries.

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The MATLAB Test and Measurement is used  for analysis which provides the tools to acquire data and automate tasks. Within MATLAB data is  controlled  and acquired  from plug-in data acquisition boards, measuring instruments, Web cameras and frame grabbers, as well as send and receive messages over CAN buses.
Once  data is acquired, it can explored interactively and perform  visualization and information analysis. Test systems are  build , designs are verified and  tasks are automatically repeat.The Test & Measurement permits  to design and control assets, for example, instruments, serial gadgets, drivers, interfaces, and so forth.
The instruments utilized for this is a tool which is an open and measuring apparatus. The Tool shows the assets like equipment, drivers, interfaces, which are  available to the tool that supports the instrument, and empowers to design and correspond with those assets. With the Test & Measurement  driver is scanned ,  device object is created  that uses that driver, set and get properties of the object, and execute functions.
This tool enables to Search for accessible equipment and drivers ,Create instrument objects ,Connect to an instrument ,Configure instrument settings ,Write information to an instrument ,Read information from an instrument & Save a log of session as a record. 

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Our Matlab Computational Finance Assignment help tutors help with topics like Data fitting: minimum least squares method, ,Solving a system of linear equations: direct methods, Jacobi method, Gauss-Seidel method.  Email Based Assignment Help :
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Financial professionals overall utilize the intuitive programming environment and prebuilt computational libraries of MATLAB® to create quantitative applications in a small amount of the time it would take them in C++ or Visual Basic.Financial Toolbox™ gives capacities to scientific demonstrating and factual examination of budgetary information. It is used for advance arrangement of monetary instruments, alternatively considering turnover and exchange costs. 
The tool kit empowers to estimate risk, dissect premium rate levels, value and premium rate subsidiaries, and measure speculation execution. Time series analysis capacities and an application allow changes or regression with missing information and change over between diverse exchanging logbooks and day-number conventions.
Key Features:
Mean-variance and CVaR-based object-oriented portfolio optimization, analysis of cash flow, risk analysis, financial time-series structuring, date math, and calendar math, SIA-compliant fixed-income security analysis, Black-Scholes, Black, and binomial option pricing, Regression and determination with missing data, GARCH estimation, simulation, and forecasting, financial charts
Financial professionals use computational finance:
Detect live data of market, structure interest rates, determining optimization problems, design quantitative models to analyze performance and minimize risk, Integrate with information sources and legacy software, Design and deploy applications to production environments, desktops, servers, and the Web.

Matlab Computational Biology Assignment Help


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Matrix models -- discrete time, linear maps:
  • Introduction to population biology
  • Linear algebra concepts: matrix multiplication and eigenvalues
  • Dominant eigenvalues and population growth
  • Euler-Lotkerra formula and root-finding

Stochastic models:
  • Coin flipping & binomial distribution 
  • Transition probabilities and Markov chains
  •  Dominant eigenvalues return
  • Central limit theorem and deterministic limits
  • Diffusion equation: applications in neuroscience of decision making

Continuous time models:
  • Ordinary differential equations and vector "arrow" fields -- visualizing flows in
  • Nullclines
  • Equilibria: Newton's method in
  • Stability and oscillations
  • Numerical solution methods,  implementation
  • Applications in gene networks, oscillators, and genetic toggle switches
  • Applications in population biology and epidemiology
  • Applications in neuroscience models and action potentials 

Fitting and testing models:
  • Least squares fits, concept of maximum likelihood
  • Model optimization in
  • Building models: model vs. parameter error

Matlab Communications Systems Assignment Help


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Communications System in MATLAB  includes  algorithms and applications  for the analysis, design, end-to-end simulation, and verification of communications systems in MATLAB . 
The  algorithms consists of  coding channel, modulation, MIMO, and OFDM, which is used for enabling  a physical layer model of the system.The Communications Systems  includes constellation and eye diagrams, bit-error-rate, and other analysis tools and scopes for validating the designs.
 These tools allows to analyze signals, visualize channel characteristics, and obtain performance metrics such as error vector magnitude (EVM). Using Communications System hardware support packages,  transmitter and receiver models are connected to radio devices and the designs are verified with over-the-air testing. 
The communication system  supports fixed-point arithmetic and C or HDL code generation.
Communications System involves simulate link-level models of communications systems.
Through simulations  system response is analyzed to the noise and interference inherent in communication channels, explore what-if cases and evaluate the tradeoffs between architectures of system and parameters, and develope expected measures of performance to evaluate real implementations of model.