Desktop Basics - MATLAB & Simulink

Desktop Basics

When you start MATLAB^®, the desktop appears in its default layout.

desktop basic

The desktop includes these panels:

Current Folder — Access your files.
Command Window — Enter commands at the command line, indicated by the prompt (>>).
Workspace — Explore data that you create or import from files.

As you work in MATLAB, you issue commands that create variables and call functions. For example, create a variable named a by typing this statement at the command line:

a = 1

MATLAB adds variable a to the workspace and displays the result in the Command Window.

a = 

     1

Create a few more variables.

b = 2

b = 

     2

c = a + b

c = 

     3

d = cos(a)

d = 

    0.5403

When you do not specify an output variable, MATLAB uses the variable ans, short for answer, to store the results of your calculation.

sin(a)

ans =

    0.8415

If you end a statement with a semicolon, MATLAB performs the computation, but suppresses the display of output in the Command Window.

e = a*b;

You can recall previous commands by pressing the up- and down-arrow keys, ↑ and ↓. Press the arrow keys either at an empty command line or after you type the first few characters of a command. For example, to recall the command b = 2, type b, and then press the up-arrow key.

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Desktop Basics - MATLAB & Simulink

Matrices and Arrays

Array Indexing - MATLAB & Simulink

Workspace Variables - MATLAB & Simulink

Text and Characters - MATLAB & Simulink

Calling Functions - MATLAB & Simulink

2-D and 3-D Plots - MATLAB & Simulink

Programming and Scripts - MATLAB & Simulink

Help and Documentation - MATLAB & Simulink

Creating, Concatenating, and Expanding Matrices - MATLAB & Simulink

Removing Rows or Columns from a Matrix

Reshaping and Rearranging Arrays

Multidimensional Arrays

Characters and Strings

Function Handles

Data Type Conversion

Data Type Identification

Add Title and Axis Labels to Chart

Create Chart with Two y-Axes

Combine Multiple Plots

Specify Axis Limits

Scripts vs. Functions

Add Functions to Scripts

Create Functions in Files

Clipping in Plots and Graphs

Creating Colorbars

Change Color Scheme Using a Colormap

How Surface Plot Data Relates to a Colormap

How Image Data Relates to a Colormap

How Patch Data Relates to a Colormap

Create and Work with Tables

Out-of-Process Execution of Python Functionality

Linear (LTI) Models

Transfer Functions

State-Space Models

Discrete-Time Numeric Models

Time-Domain Response Data and Plots

Time-Domain Responses of Discrete-Time Model

Time-Domain Responses of MIMO Model

Time-Domain Responses of Multiple Models

Introduction: PID Controller Design

Introduction: Root Locus Controller Design

Introduction: Frequency Domain Methods for Controller Design

DC Motor Speed: PID Controller Design

DC Motor Position: PID Controller Design

Cruise Control: PID Controller Design

Suspension: Root Locus Controller Design

Aircraft Pitch: Root Locus Controller Design

Inverted Pendulum: Root Locus Controller Design

Ball & Beam: Root Locus Controller Design

Introduction: System Modeling

Get Started with Deep Network Designer

Create Simple Image Classification Network Using Deep Network Designer

Build Networks with Deep Network Designer

Classify Image Using GoogLeNet

Classify Webcam Images Using Deep Learning

Transfer Learning with Deep Network Designer

Train Deep Learning Network to Classify New Images

Deep Learning Processor Customization and IP Generation

Prototype Deep Learning Networks on FPGA

Deep Learning Processor Architecture

Deep Learning INT8 Quantization

Compiler Output

Quantization of Deep Neural Networks

Custom Processor Configuration Workflow

Estimate Performance of Deep Learning Network by Using Custom Processor Configuration

Generate Custom Bitstream

dlhdl.Workflow class

Preprocess Images for Deep Learning

Preprocess Volumes for Deep Learning

Transfer Learning Using AlexNet

Time Series Forecasting Using Deep Learning

Create Simple Sequence Classification Network Using Deep Network Designer

Classify Image Using Pretrained Network

Create Simple Image Classification Network

Design and simulation of a boost converter

Design and simulation of a boost converter 2

Machine Learning in MATLAB

Train Classification Models in Classification Learner App

Train Regression Models in Regression Learner App

Distribution Plots

Explore the Random Number Generation UI

Design of Experiments

Machine Learning Models

Logistic regression

Logistic regression create generalized linear regression model - MATLAB fitglm 2

Support Vector Machines for Binary Classification

Support Vector Machines for Binary Classification 2

Support Vector Machines for Binary Classification 3

Support Vector Machines for Binary Classification 4

Support Vector Machines for Binary Classification 5

Assess Neural Network Classifier Performance

Naive Bayes Classification

ClassificationTree class

Discriminant Analysis Classification

Ensemble classifier

ClassificationTree class 2

Train Generalized Additive Model for Binary Classification

Train Generalized Additive Model for Binary Classification 2

Classification Using Nearest Neighbors

Classification Using Nearest Neighbors 2

Classification Using Nearest Neighbors 3

Classification Using Nearest Neighbors 4

Classification Using Nearest Neighbors 5

Linear Regression

Linear Regression 2

Linear Regression 3

Linear Regression 4

Nonlinear Regression

Nonlinear Regression 2

Visualizing Multivariate Data

Generalized Linear Models

Generalized Linear Models 2

RegressionTree class

RegressionTree class 2

Neural networks

Gaussian Process Regression Models

Gaussian Process Regression Models 2

Understanding Support Vector Machine Regression

Understanding Support Vector Machine Regression 2

RegressionEnsemble

Using Signal Analyzer App

Extract Voices from Music Signal

Align Signals with Different Start Times

Find a Signal in a Measurement

Find Peaks in Data

Extract Features of a Clock Signal

Filtering Data With Signal Processing Toolbox Software

Take Derivatives of a Signal

Find Periodicity Using Frequency Analysis

Find and Track Ridges Using Reassigned Spectrogram

Classify ECG Signals Using Long Short-Term Memory Networks

Waveform Segmentation Using Deep Learning

Label Signal Attributes, Regions of Interest, and Points

Introduction to Streaming Signal Processing in MATLAB

Filter Frames of a Noisy Sine Wave Signal in MATLAB

Filter Frames of a Noisy Sine Wave Signal in Simulink

Lowpass Filter Design in MATLAB

Tunable Lowpass Filtering of Noisy Input in Simulink

Signal Processing Acceleration Through Code Generation

Signal Visualization and Measurements in MATLAB

Estimate the Power Spectrum in MATLAB

Design of Decimators and Interpolators

Multirate Filtering in MATLAB and Simulink

Estimate the Transfer Function of an Unknown System

View the Spectrogram Using Spectrum Analyzer

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