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Matlab Tutorial - 25 - Calculating the Vector Dot Product and Cross Product
 
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Get more lessons like this at http://www.MathTutorDVD.com Learn how to calculate the dot product between two vectors using matlab. We will also learn how to enter and calculate the vector cross product using matlab.
Views: 260 mathtutordvd
1.Matlab/Simulink-commonly used blocks Constant & Product Blocks
 
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Please watch: "Part-2 Design and simulatio of 3 phase half wave controlled rectifier" https://www.youtube.com/watch?v=f8eQKZBV-io --~-- This video shows how to work with constant and product blocks in matlab/simulink software
Views: 781 Nageswar J
Memristor-Based Analog Computation and Neural Network Classification with a Dot Product Engine
 
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Large memristor arrays composed of hafnium oxide are demonstrated with suitability for computing matrix operations at higher power efficiency than digital systems. The nonmemory application of memristors is performed in an analog computing platform. Computational operations with 6-bit equivalent precision are shown and utilized to directly compute neural network inference within a memristor crossbar. This is reported by Miao Hu, Catherine E. Graves, Can Li, Yunning Li, Ning Ge, Eric Montgomery, Noraica Davila, Hao Jiang, R. Stanley Williams, J. Joshua Yang, Qiangfei Xia, and John Paul Strachan in the article https://doi.org/10.1002/adma.201705914. To know more, please go to the Advanced Materials homepage.
Field-Oriented Control with Simulink, Part 2: Modeling Motor, Inverter, and Controller
 
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Learn more about field-oriented control: http://bit.ly/2QrXMMd Learn how to model a typical field-oriented controller architecture in Simulink® and Simscape Electrical™. This example shows field-oriented control of an induction motor. - Free Trial Software for Power Electronics Control Design: http://bit.ly/2P77UJK The video shows how to use Simscape Electrical to build a model that includes a squirrel cage asynchronous machine, a power inverter, voltage source, a power transformer, and a rectifier. The video explains how you can change parameters of various blocks in the model including motor parameters, switching devices in the inverter, and parameters of the transformer to customize the model for your application. It demonstrates how phase currents and phase voltages can be measured from the model. It also shows how to model a mechanical load on the motor shaft. A proper choice of simulation solver is discussed to achieve the right balance of simulation speed and accuracy. The video then explains how to model various components of a field-oriented controller. Those include proportinal-integral (PI) controllers for the inner current loops and outer speed and flux loops, Park and Clarke transforms, and space vector PWM generator, as well as an observer for estimating rotor position and speed. Get a free product Trial: https://goo.gl/ZHFb5u Learn more about MATLAB: https://goo.gl/8QV7ZZ Learn more about Simulink: https://goo.gl/nqnbLe See What's new in MATLAB and Simulink: https://goo.gl/pgGtod © 2018 The MathWorks, Inc. MATLAB and Simulink are registered trademarks of The MathWorks, Inc. See www.mathworks.com/trademarks for a list of additional trademarks. Other product or brand names maybe trademarks or registered trademarks of their respective holders.
Views: 1521 MATLAB
Dot Product Review
 
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This video is a review of the dot product. It includes how to calculate the scalar dot product and the angle between two vectors. Engineer It is a video series created primarily to supplement engineering classes at CSU Chico, but also to expose non-engineers to these same concepts in an understandable way. For more information please visit the official website at www.csuchico.edu/engineerit
Views: 523 EngineerItProgram
DOT and CROSS products | Matlab
 
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Theory of dot and cross products, and it's calculations in Matlab
Views: 25 raidar ali
Simulink Product
 
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Views: 73 TeraSoftTW
Matlab difference between  RMS AND AVERAGE in sinusoidal waveform
 
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for more electrical and electronics simulation video go to youtube channel - rkk salem web site http://rkksalem.weebly.com/
Views: 1973 karthik kumar
CAS DOT Lab -100- Memristor based neuromorphic computing
 
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By Vishnu Jujhala and Vinod Kumar, Graduate Student At Texas Tech University, Spring 2015
Views: 1412 Tooraj Nikoubin
Dot and Cross Product in Matlab
 
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Dot and Cross Product in Matlab Here, you'll learn about dot and cross product of vectors, dot and cross product of vectors in hindi, dot and cross product khan academy, dot and cross product examples, cross multiply, cross product, online matlab compiler, scalar product, online matlab compiler, vector multiplication, dot product of two vectors, simulink. Download Matlab Software Here: https://bulkbytes.blogspot.com/2017/10/matlab-2013a-with-serial-key-full.html Subscribe our channel for more videos: https://www.youtube.com/channel/UCxeac6DPx87DO0wK2udQtoQ?view_as=subscriber?sub_confirmation=1 #matlab #dotcrossproduct #dotcrossmatlab #matlabtutorial
Views: 7 Math with Umair
Scalar product and Dot product in Matlab | Matlab Tutorials | MATLAB Programming : By Nehal
 
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- NEHAL JAIN ([email protected]) (works at qcfinance.in) Learning Elementary Matlab course – (Personalized 5 hours of Live interactive classes to help you learn basics of MATLAB) We offer one on one live classes with customized topics to help our learners. We provide MATLAB for finance consultancy & also take MATLAB projects. Projects are charged according to hours taken to complete them. http://www.wiziq.com/course/67041-learning-elementary-matlab-one-to-one-classes http://qcfinance.in/learning-elementary-matlab-one-on-one-course/ https://www.udemy.com/course-manage/show-course-url/?courseId=321498 Email ID - [email protected] Skype ID - qcfinancein Our Website - http://qcfinance.in/ Our Blog - http://stockcreditfinancecfa.blogspot.in/ Our Courses- http://www.wiziq.com/course/67041-learning-elementary-matlab-one-to-one-classes https://www.wiziq.com/course/77609-introduction-to-r https://www.wiziq.com/course/7225-matlab-for-financial-engineering http://www.wiziq.com/course/70342-one-on-one-course-on-quant-finance-interviews-preparation http://www.wiziq.com/course/48106-one-on-one-training-to-prepare-for-frm-part-ii-exam http://www.wiziq.com/course/19620-vba-for-financial-engineering-and-modeling http://www.wiziq.com/course/7526-bloomberg-assessment-test-bat-exam-prep http://www.wiziq.com/course/71364-an-introduction-to-technical-analysis
Views: 134 Nehal Jain
Field-Oriented Control with Simulink, Part 1: What Is Field-Oriented Control?
 
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Learn more about field-oriented control: http://bit.ly/2QrXMMd Learn how field-oriented control provides high-performance torque or speed control for various motor types, including induction motor, permanent magnet synchronous machines (PMSMs), and brushless DC (BLDC) motors. - Free Trial Software for Power Electronics Control Design: http://bit.ly/2P77UJK The video introduces a typical field-oriented controller architecture and explains various components involved. Those include AC motor, power inverter, Clarke, Park, and inverse Park transforms, inner-loop current controller, optional outer-loop speed or flux controller, space vector modulator algorithm, and an optional rotor speed and position observer. The video explains how Park and Clarke transforms are used to simplify computations by converting AC current and voltage waveform into DC signals. Continuous and discontinuous modulation schemes for space vector modulation are discussed. Get a free product Trial: https://goo.gl/ZHFb5u Learn more about MATLAB: https://goo.gl/8QV7ZZ Learn more about Simulink: https://goo.gl/nqnbLe See What's new in MATLAB and Simulink: https://goo.gl/pgGtod © 2018 The MathWorks, Inc. MATLAB and Simulink are registered trademarks of The MathWorks, Inc. See www.mathworks.com/trademarks for a list of additional trademarks. Other product or brand names maybe trademarks or registered trademarks of their respective holders.
Views: 2727 MATLAB
MATLAB demonstration computing dot products and cross products of 3D vectors in Calc 3
 
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MATLAB demonstration computing dot products and cross products of 3D vectors in Calc 3
Views: 102 Calc3 MathGeek
Automatic Tuning of Field-Oriented Controllers for an Induction Motor
 
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Implement and automatically tune a field-oriented control system that controls the flux and torque of a three-phase induction motor. Learn more about Field-Oriented Control: http://bit.ly/2BiB8Q5 Learn more about Motor Control Design: http://bit.ly/2BeNc4U The control system consists of four PI controllers. The rotor speed and flux controllers in the outer loop provide references to the current controllers in the inner loop using the measured rotor speed and three-phase stator current as well as the Clarke and Park transformations. The four PI controllers are tuned using the Closed-Loop PID Autotuner block in a single simulation. This block injects an excitation signal during closed-loop plant operation to estimate the plant frequency response and automatically tune the PID gains. Based on the PID outputs, a PWM Generator module is used to generate the gate control pulses for the semiconductor switches in the machine-side power inverter, such that the desired flux and torque specifications are met. The Closed-Loop PID Autotuner block is part of Simulink Control Design™ since MATLAB® R2018a and the induction motor and power converters have been modeled in Simscape Power Systems™. Get a free product Trial: https://goo.gl/ZHFb5u Learn more about MATLAB: https://goo.gl/8QV7ZZ Learn more about Simulink: https://goo.gl/nqnbLe See What's new in MATLAB and Simulink: https://goo.gl/pgGtod © 2018 The MathWorks, Inc. MATLAB and Simulink are registered trademarks of The MathWorks, Inc. See www.mathworks.com/trademarks for a list of additional trademarks. Other product or brand names maybe trademarks or registered trademarks of their respective holders.
Views: 1513 MATLAB
Understanding Control Systems, Part 4: Simulating Disturbance Rejection in Simulink
 
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This demonstration uses a car to show how you can simulate open- and closed-loop systems in Simulink®. Download model: http://bit.ly/2Qau7XO Watch other MATLAB Tech Talks: https://goo.gl/jD0uOH Get a free Product Trial: https://goo.gl/C2Y9A5 First, you will learn how to model and tune open-loop systems. The goal of the demonstration is to maintain the speed of a car. Then, you’ll explore the behavior of the open-loop system in the presence of a disturbance. To illustrate disturbance rejection, the video shows how to model and simulate a feedback control system . You will gain insight into how feedback control compensates for disturbance. You’ll investigate signals such as error (in this example, the error is the difference between the measured and desired output), actuating signal (here, the actuating signal is the pedal’s position) and system output (in this example, the output is speed).
Views: 26432 MATLAB
How to find 3D rotation matrix between two coordinate systems matlab?Using PCA?
 
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http://www.mediafire.com/file/ak5lgikam3er5je/PCA.rar/file https://www.mathworks.com/matlabcentral/answers/400250-rotation-matrix-3d-point-data -------------------------------------------------------------------------------------------- clear;clc; load('data.txt');figure(1);scatter3(data(:,1),data(:,2),data(:,3),'.') %% hold on;scatter3(42.706,88.286,70.656,'diamond','r') PCA=pca(data);%use Principal component analysis method e1=PCA(:,1)'; e2=PCA(:,2)' ;e3=PCA(:,3)'; % 3 principal vector(3 eigenvector) of "data" n1=[1 0 0] ; n2=[0 1 0] ; n3=[0 0 1]; % 3 unit vector Ox,Oy,Oz %[PCA,~,lamda] = pca(data);%use this syntax to find eigenvalue of data. lamda is eigenvalue corresponding to 3 eigenvector (e1,e2,e3) % --------Conclusion1: each eigvector(each Principal component)is unit vector(e1,e2,e3) ---------------------% % --------Conclusion2: each eigvector(each Principal component) is always perpendicular to each other--------% % --------It means that "dot product" or "scalar product" of each eigvector is equal to zero-----------------% % --------Using the below syntax to find "scalar product" of 2 vector----------------------------------------% % dot(e1,e2); % dot(e1,e3); % dot(e2,e3); % --------Conclusion3: norm(||..x..||)of each eigvector(e1,e2,e3) is always equal to one-----% % --------Using the below syntax to find "norm" of each eigvector----------------------------% % norm(e1); % norm(e2); % norm(e3); %% transformation matrix from "e" space to "n" space R=[e1;e2;e3]; % rotation matrix. % match with xyz (e1//n1, e2//n2, e3//n3) % R=[e3;e2;e1]; % If e1//n3, e2//n2, e3//n1 %% newdata=(R*data')'; figure(2); n = fitNormal(newdata,1); grid on; % https://jp.mathworks.com/matlabcentral/fileexchange/37775-plane-fitting-and-normal-calculation % create the input data: data = rand(50,3)*100; data(:,3) = data(:,1) * .4 + data(:,2) * .6 + rand(50,1); -------------------------------------GENERAL CASE------------------------------------------ -------------------------------%%%%%%%%%%%%------------------------------------------ %% Load input 3D data clear;clc;filename = 'test.txt'; inputfile = importfile(filename); P = inputfile(:,1:3);%get data=coordinate(x,y,z) from set of data x = P(:,1) ; y = P(:,2) ;z = P(:,3) ; % get (x,y,z) coordinate x0 = x-mean(x) ; y0 = y-mean(y) ; z0 = z-mean(z) ; % remove mean P1 = [x0 y0 z0] ; %this step to bring the coord of P near to the origin. The new coord will be created scatter3(P1(:,1),P1(:,2),P1(:,3),'b.');%plot new coord of P1 HA=[min(P1(:,1)) min(P1(:,2)) max(P1(:,3))+1];%just for better visualaztion hold on;scatter3(HA(:,1),HA(:,2),HA(:,3),'g.');%just for better visualaztion %% Finding principal vector of 3D data P PCA=pca(P); e1=PCA(:,1)'; e2=PCA(:,2)' ;e3=PCA(:,3)'; % 3 principal vector(3 eigenvector) of "input data" n1=[1 0 0] ; n2=[0 1 0] ; n3=[0 0 1]; % 3 unit vector Ox,Oy,Oz %% transformation matrix from "e" space to "n" space R=[e2;e1;e3]; % rotation matrix , match with xyz (e1//n2, e2//n1, e3//n3) % R=[e1;e2;e3]; % rotation matrix , match with xyz (e1//n1, e2//n2, e3//n3) % R=[e3;e2;e1]; % If e1//n3, e2//n2, e3//n1 %% Finding the new rotate data newdata1=(R*P1')';%new data corresponding to P1 coordinate hold on; scatter3(newdata1(:,1),newdata1(:,2),newdata1(:,3),'r.'); newdata=[newdata1(:,1)+mean(x),newdata1(:,2)+mean(y),newdata1(:,3)+mean(z)]; %% Plot the original & rotation 3D data figure;scatter3(P(:,1),P(:,2),P(:,3),'b.'); hold on;scatter3(newdata(:,1),newdata(:,2),newdata(:,3),'r.'); HA=[min(P(:,1)) min(P(:,2)) max(P(:,3))+1];%just for better visualaztion hold on;scatter3(HA(:,1),HA(:,2),HA(:,3),'g.');%just for better visualaztion legend('original data(P)','rotated data(newdata)');title({'Plot the rotation matrix 3D point data';'(FINAL RESULT)'}); -------------------------------------------------------------------------------------- See more detail in below web to understand the formula of covariance: https://www.itl.nist.gov/div898/handbook/pmc/section5/pmc541.htm
Views: 2195 ha
Battery Management System Development in Simulink
 
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Learn about Developing Battery Management Systems with Simulink and Model-Based Design: http://bit.ly/2DRm9MJ Battery management systems balance the state of charge of individual cells and ensure the proper charging, discharging, and safe operation of rechargeable battery packs. Get free resources on Battery Management systems: http://bit.ly/2P1PA4A Download a trial: http://bit.ly/2P77UJK Simulink® is used to create a model of a three-cell battery pack that is charged using a constant-current constant-voltage (CCCV) profile, and simultaneously equalizes the state of charge of the cells using on-charge passive balancing. The balancing logic is designed in Stateflow®, and it is ready for automatic C-code generation for hardware implementation." © 2018 The MathWorks, Inc. MATLAB and Simulink are registered trademarks of The MathWorks, Inc. See www.mathworks.com/trademarks for a list of additional trademarks. Other product or brand names maybe trademarks or registered trademarks of their respective holders.
Views: 4033 MATLAB
Vector Dynamics - Coordinate Table
 
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In this video I explain how to use the Dot Product to help change coordinate systems.
Views: 695 TheMrHandyMan
Dot vs Cross Product
 
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This video shows the difference between the dot and cross products. With the vectors [a,b,c] and [x,y,z], the dot product results in the scalar a*x + b*y + c*z. The cross product results the vector [b*z-c*y, c*x-a*z, a*y-b*x].
Views: 2948 Edward Shore
IEA216 Mathematical Operations in Matlab
 
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Addition, subtraction, multiplication, division, and exponentiation in Matlab. Software: Matlab Version: 2017a. Topics: 1:30 - Addition (+) operator 4:10 - Multiplication (*) operator 5:28 - The 'clear' and 'clc' commands 6:35 - Multiplication (*), the dot product 8:32 - Multiplication (*), element by element 9:05 - Division (/,\) operator, "left" and "right" divisions 10:21 - Solving multiple linear equations using the "right" division 12:12 - Division (/) operator, element by element 12:30 - Division by zero 12:56 - Exponentiation (*) operator
Views: 384 Yusri Yusup
Matlab Vector Operations  - Beginner's Tutorial (3/15)
 
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http://adampanagos.org Matlab vector examples are defined and various vector operations (component-wise operations, scalar product, etc.) are examined and performed in Matlab. If you enjoyed my videos please "Like", "Subscribe", and visit http://adampanagos.org to setup your member account to get access to downloadable slides, Matlab code, an exam archive with solutions, and exclusive members-only videos. Thanks for watching!
Views: 1475 Adam Panagos
Introduction to 3D Animation using Simulink and V-Realm Builder - Part 2
 
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This is part 2 of my tutorial ! I cover 1) Introduction to Simulink 2) Connect VRML world to Simulink model 3) Configuring model for flight 4) Post processing results in MATLAB as an array
Views: 3114 VDEngineering
Distillation PID Control in Simulink (MATLAB)
 
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The objective is to control the composition of the product by adjusting the reflux ratio for a continuous distillation column. The Simulink simulator is available at http://apmonitor.com/che436/uploads/Main/sp10.zip - this simulator is used to generate a step response and to add a PID controller for testing. See http://apmonitor.com/pdc/index.php/Main/DistillationControl for the full problem statement.
Views: 2147 APMonitor.com
Parabolic Collector for Gas Turbine CO2 Power Generation Simulink model
 
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Learn how to deal with such models. This model is about power generation by the use of Parabolic Trough Collector system (PTC) combined with Gas Turbine Cycle (GTC) with CO2 working gas. Therminol-VP1 heat transfer oil is used through the PTC cycle. User can assign the grid needed power in order to obtain all design aspects such as: 1-PTC field design (area, Loops, etc..). 2-Design aspects for GTC. 3-Energy, and Exergy streams are calculated. 4-CO2 fluid is used through the GTC. 5-Therminol-VP1 HTO is used through the PTC cycle. All cycles are prepared for dynamic and fixed point modeling. All cycles are designed for electric power generation. Model download: https://www.redslibrary.com/product-page/ptc-for-gtc-with-co2-power-generation Shop: https://www.redslibrary.com/shop Follow us: https://www.facebook.com/redslibrary/
Views: 148 REDS Library
ETAS INCA-VLINK -- Blockset for Measurement and Calibration on Windows
 
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INCA-VLINK a allows the deployment of Simulink® models as executable programs running on standard Windows PCs.This video introduces the main product features and shows how to work with the product. Since this video contains large screen recordings, we recommend to select a high resolution (Full Screen) and best video quality (HD). More information on ETAS INCA-VLINK: http://www.etas.com/inca_vlink
Views: 2547 ETAS
Matlab - Sect 47 - Matrix Norm, EigenValues, and the Characteristic Polynomial
 
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Math Tutor Series for Matlab Programming.
Views: 1876 Ahmed Hamdy
Sect 01|   The User Interface   Part 1
 
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This Course Focusing on the Essential Skills you should have if you are using or intended to use MATLAB, the course is about 61 tutorial each of them not more than 15 min, and includes the followings: Sect 1 - The User Interface - Part 1 Sect 2 - The User Interface - Part 2 Sect 3 - The User Interface - Part 3 Sect 4 - Using the Help Menus Sect 5 - Basic Arithmetic and Order of Operations Sect 6 - Exponents and Scientific Notation Sect 7 - Working with Fractions and the Symbolic Math Toolbox - Part 1 Sect 8 - Working with Fractions and the Symbolic Math Toolbox - Part 2 Sect 9 - Defining and Using Variables Sect 10 - Adding Comments to your Matlab Code Sect 11 - Clearing Variables Sect 12 - Adjusting the Display Precision for Calculations Sect 13 - Creating and Storing Values in Symbolic Variables Sect 14 - Performing Calculations with Symbolic Variables Sect 15 - Factorial, Square Roots, and nth Roots Sect 16 - Trigonometric Functions and their Inverses Sect 17 - Hyperbolic Functions and their Inverses Sect 18 - Exponentials and Logarithms Sect 19 - Basic Calculations with Complex Numbers Sect 20 - Calculating the Magnitude and Angle of Complex Numbers Sect 21 - Trig Functions, Logarithms, and Exponentials with Complex Numbers Sect 22 - Complex Numbers and the Symbolic Math Toolbox Sect 23 - Inputting Vectors and Extracting Components Sect 24 - Adding and Subtracting Vectors and Multiplying Vectors by a Scalar Sect 25 - Calculating the Vector Dot Product and Cross Product Sect 26 - Finding the Mean, Sum, and Length of a Vector Sect 27 - Extracting a Subset of Vector Elements Sect 28 - Creating Vectors with Evenly Spaced Elements Sect 29 - Joining Vectors Together Sect 30 - Multiplying and Dividing Vectors Element-by-Element Sect 31 - Applying Math Functions to Elements of a Vector Sect 32 - Creating Vectors with Random Elements Sect 33 - Calculating Mean, Median, and Standard Deviation of Data in a Vector Sect 34 - Working with Vectors using the Symbolic Math Toolbox Sect 35 - Inputting Matrices and Extracting Elements - Part 1 Sect 36 - Inputting Matrices and Extracting Elements - Part 2 Sect 37 - Adding and Subtracting Matrices and Multiplying by a Scalar Sect 38 - Multiplying Matrices Sect 39 - Multiplying and Dividing Matrices Element-by-Element Sect 40 - Finding the Length, Size, Sum, and Number of Elements in a Matrix Sect 41 - Joining Matrices Together Sect 42 - Apply Mathematical Functions to Matrices Sect 43 - Creating an Identity Matrix Sect 44 - Matrix Transpose, Diagonal Elements, and LU Decomposition Sect 45 - Solving A System of Equations using Row Reduced Echelon Form Sect 46 - Matrix Determinant, Inverse, Trace, and Rank Sect 47 - Matrix Norm, EigenValues, and the Characteristic Polynomial Sect 48 - Working with Matrices and the Symbolic Math Toolbox Sect 49 - Solving Algebraic Equations Sect 50 - Solving Systems of Linear Equations Sect 51 - Solving Algebraic Equations Symbolically Sect 52 - Solving Systems of Algebraic Equations Symbolically Sect 53 - Defining Mathematical Functions Sect 54 - Taking Derivatives in Calculus Sect 55 - Evaluating Derivatives at a Point Sect 56 - Taking Partial Derivatives in Calculus Sect 57 - Indefinite and Definite Integrals Sect 58 - Taking Limits in Calculus Sect 59 - Basic Scatter Plots Sect 60 - Plotting Functions Sect 61 - Changing Plot Appearance
Views: 177 TO Courses
Code Generation Improvements for Vision and ADAS - Coder Summit 2018
 
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MathWorks coder products for MATLAB®, Simulink®, and Stateflow® share a common coder engine that is increasingly optimized for design patterns used by engineers in computer vision and automated driving/ADAS applications. Learn more about embedded system solutions: https://goo.gl/kCqw3F Using a series of code differences, you can observe dramatic improvements in C code generated from MATLAB Coder™, Simulink Coder™, and Embedded Coder® involving large matrix constants, loop invariant code, variable size matrices, and single iterations. Learn more about Embedded Coder: https://goo.gl/4uLCr2 This presentation is from Coder Summit Talks, which are live recordings of developers and engineers debuting their best MATLAB and Simulink coder optimizations and examples at an annual technical interchange. Try the Production Code Generation Evaluation Kit: https://goo.gl/pC8zgk © 2018 The MathWorks, Inc. MATLAB and Simulink are registered trademarks of The MathWorks, Inc. See www.mathworks.com/trademarks for a list of additional trademarks. Other product or brand names maybe trademarks or registered trademarks of their respective holders.
Views: 998 MATLAB
CEMWARE Product
 
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CEMWARE Product
Views: 63 dankim090509
Building a Radar Data Cube with MATLAB and Phased Array System Toolbox
 
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Learn more about Phased Array System Toolbox: http://www.mathworks.com/videos/phase... Download a Free Trial of Phased Array System Toolbox: https://www.mathworks.com/programs/tr... Build a radar data cube for two systems: an eight-element uniform linear array with a single radar target, and an array with 121 elements mounted on the surface of a sphere and 20 targets. Phased Array System Toolbox™ provides algorithms and apps for the design, simulation, and analysis of sensor array systems in radar, sonar, wireless communications, and medical imaging applications. The system toolbox includes pulsed and continuous waveforms and signal processing algorithms for beamforming, matched filtering, direction of arrival (DOA) estimation, and target detection. It also includes models for transmitters and receivers, propagation, targets, jammers, and clutter. The system toolbox lets you model the dynamics of ground-based, airborne, or ship-borne multifunction radar systems with moving targets and platforms. You can design end-to-end phased array systems and analyze their performance under different scenarios using synthetic or acquired data. The toolbox apps let you explore the characteristics of sensor arrays and waveforms and perform link budget analysis. In-product examples provide a starting point for implementing custom phased array systems.
Views: 4386 MATLAB
6.3: Steering Behaviors: Arrive - The Nature of Code
 
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This video covers the arriving at a target, i.e. slowing down on approach. Read along: http://natureofcode.com/book/chapter-6-autonomous-agents/#chapter06_section4 http://www.red3d.com/cwr/steer/Arrival.html https://github.com/shiffman/The-Nature-of-Code-Examples/tree/master/Processing/chp6_agents/NOC_6_02_Arrive Help us caption & translate this video! http://amara.org/v/Qbvi/
Views: 13274 The Coding Train
Detecting division-by-zero with QGen
 
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In this video, we use QGen static analysis capabilities to detect a potential division by zero.
Views: 613 Matteo Bordin
BETA CAE Systems - Simulation Solutions
 
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BETA CAE Systems is a simulation solutions provider, dedicated to the development of state of the art software systems for CAE. For almost 30 years, we have been developing tools and delivering services for the front-runners in numerous sectors by listening to their needs and taking up even the most demanding challenges. Learn more: http://www.beta-cae.com/
Views: 1388 BETA CAE Systems
UE4 RayCast Vehicle Tutorial | Clutch/Torque Converter
 
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Сlutch - a necessary element of the transmission. How to implement it, will be discussed in this video. Сцепление - необходимый элемент трансмиссии. О том, как его реализовать, пойдет речь в данном видео. useful links https://www.gamedev.net/forums/topic/694941-clutch-modelling-help/ https://www.mathworks.com/help/simulink/examples/building-a-clutch-lock-up-model.html https://x-engineer.org/automotive-engineering/drivetrain/coupling-devices/calculate-torque-capacity-clutch/
ANNA UNIVERSITY SIMULATION LAB-MATLAB: Matrices (Addition, Subtraction, Transpose and Inverse)
 
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To input the value of the matrix a=[1 2 3;4 5 6;7 8 9]; b=[9 8 7;6 5 4;3 2 1]; To add a+b To subtract b-a To find transpose a' To find the inverse inv(a)
Views: 828 NishantTeaches
19 Linear Algebra in Matlab Part 2 Kronecker Tensor Product | Matrix Norm | Multi Thread Computation
 
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MATLAB MATHEMATICS IN MATLAB LINEAR ALGEBRA PART 2 Kronecker Tensor Product, What is Vector Norm, Matrix Norm, Multi thread Computation with Linear algebra functions, System of linear equations, What is Mrdivide and Mldivide, Using Multi thread Computation with system of linear equation, Iterative methods for solving of linear equations, Inverse and Determinants, What is Pseudo Inverse, Video by Edupedia World (www.edupediaworld.com), Online Education, All Right Reserved.
Views: 2497 Edupedia World
How to find determinant & inverse of a Matrix in MATLAB
 
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How to find determinant & inverse of a Matrix in MATLAB?
MATLAB Programming Tutorial #17 Basics of Linear Algebra
 
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MATLAB Programming Tutorial #17 Basics of Linear Algebra Complete MATLAB Tutorials @ https://goo.gl/EiPgCF
Views: 1409 Xoviabcs
Matlab Video Tutorial:  Multiplying Matrices and Vectors
 
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http://www.FreedomUniversity.TV. A series of tutorial videos and examples on using matlab to solve problems. For questions, please contact Professor Santiago at [email protected] or visit the above website.
Views: 68585 John Santiago

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