MATLAB Examples

Welcome to this MATLAB Video tutorial. If you have never used MATLAB before, this demonstration will get you started and show you where to go to next to learn more.

Copyright 2013 The MathWorks, Inc.Published with MATLAB® R2013a

Use the MATLAB® Support Package for Arduino® Hardware to control a HC-SR04 ultrasonic ranging module capable of measuring distances in the 2cm to 400cm range.

This example was authored by the MathWorks community.

This scripts demonstrates the capabilities of the heatmap visualization function.

If you have a set of N points on a cartesian plane, there will always exist an N-1th order polynomial of the form y = a_0 + a_1.x + a_2.x^2 + ... a_n-1.x^(n-1) which passes through all the points.

F. Moisy, 9 july 2008. University Paris Sud.

Some basic examples on how to use mutliple input set functions:

Build a digital voltmeter using MATLAB® Support Package for Raspberry Pi® Hardware.

All the scripts provided are used in Partial Differential Equation Methods for Image Inpainting (Carola-Bibiane Schoenlieb, Cambridge University Press, 2015):

Use the MATLAB® Support Package for Arduino® Hardware to communicate with DS18B20 temperature sensor and DS2431 EEPROM

Animates the vibration of a membrane, captures a series of screen shots, and saves the animation as a GIF image file.

This script reads in an image file and then attempts to find a green object in the image. It is designed to find one green ball and highlight that ball on the original image

The function 'readImages' reads dicom image data from an image file or folder. Important attributes are stored in a convenient structure, which is used as the input for many other MATLAB

Step through and execute this script cell-by-cell to verify a cell array implementation of the List Abstract Data Type (ADT).

Example spreadsheet from a brain imaging study

I'm positive that some simple UML-diagrams could help us organizing our Matlab code. See UmlAsSketch by Martin Fowler.

Mark Text -> change Font -> change Background color

(c) Viktor Witkovsky (witkovsky@savba.sk) Ver.: 31-Jul-2014 18:27:32

How to create subplots in MATLAB®.

This function creates axes in tiled positions. It is similar to subplot, but uses the entire figure window with no space between subplots. The name smplot is used to invoke "Small Multiples"

Is derived from Gerard Schuster's MATLAB example and book Seismic Interferometry

This file demonstrates how to use the Par class object to time the execution time of each PARFOR loop. Here are the steps.

These are the files used in the webinar on Feb. 23, 2011. This file provides a brief description of the contents of the demo files and the steps needed to download the public data sources for use

A MATLAB application from the field of systems biology was chosen for experimental runs. The application was created using SimBiology® which extends MATLAB® with functionality for

In parallel computing, communication between workers extracts a heavy cost and therefore a rule of thumb is to keep processing local. But certain array operations, such as averaging over a

This demo calculates returns the risk-return relationship in the stock portfolio that is optimal in the mean-variance sense. covMat and expRet are the covariance and mean returns of a

Looks at how we can benchmark the solving of a linear system on the GPU. The MATLAB® code to solve for x in A*x = b is very simple. Most frequently, we use matrix left division, also known as

Benchmark solving a linear system on a cluster. The MATLAB® code to solve for x in A*x = b is very simple. Most frequently, one uses matrix left division, also known as mldivide or the backslash

In this example, we show how to benchmark an application using independent jobs on the cluster, and we analyze the results in some detail. In particular, we:

Runs a MATLAB® benchmark that has been modified for the Parallel Computing Toolbox™ and executes it on the client machine. Fluctuations of 5 or 10 percent in the measured times of repeated

Looks at why it is so hard to give a concrete answer to the question "How will my (parallel) application perform on my multi-core machine or on my cluster?" The answer most commonly given is "It

Runs a MATLAB® benchmark that has been modified for Parallel Computing Toolbox™. We execute the benchmark on our workers to determine the relative speeds of the machines on our distributed

How arrayfun can be used to run a MATLAB® function natively on the GPU. When the MATLAB function contains many element-wise operations, arrayfun can provide improved performance when

Use pagefun to improve the performance of applying a large number of independent rotations and translations to objects in a 3-D environment. This is typical of a range of problems which

Uses Conway's "Game of Life" to demonstrate how stencil operations can be performed using a GPU.

Uses Parallel Computing Toolbox™ to perform a two-dimensional Fast Fourier Transform (FFT) on a GPU. The two-dimensional Fourier transform is used in optics to calculate far-field

Measure some of the key performance characteristics of a GPU.

Uses Parallel Computing Toolbox™ to perform a Fast Fourier Transform (FFT) on a GPU. A common use of FFTs is to find the frequency components of a signal buried in a noisy time-domain signal.

Switch between the different random number generators that are supported on the GPU and examines the performance of each of them.

Fit an exponential model to data using the fit function.

Use anovan to fit models where a factor's levels represent a random selection from a larger (infinite) set of possible levels.

Fit and compare polynomials up to sixth degree using Curve Fitting Toolbox, fitting some census data. It also shows how to fit a single-term exponential equation and compare this to the

Machine learning techniques are often used for financial analysis and decision-making tasks such as accurate forecasting, classification of risk, estimating probabilities of default,

This script contains the examples shown in the webinar titled Optimization Tips and Tricks: Getting Started using Optimization with MATLAB presented live on 21 August 2008. To view the

The aim of this analysis is to characterize the dose response behavior of 4 different drug candidates in a population. The objective of this analysis is investigate the how the treatments

This demo is an example of performing data mining on historical fuel economy data. We have data from various cars built from year 2000 up to 2012.

Simulates the movements of a swarm to minimize the objective function

Human activity sensor data contains observations derived from sensor measurements taken from smartphones worn by people while doing different activities (walking, lying, sitting etc).

Generate a nonlinear classifier with Gaussian kernel function. First, generate one class of points inside the unit disk in two dimensions, and another class of points in the annulus from

Teaches how to use the Metropolis algorithm to simulate the Ising model of a ferromagnet in MATLAB.

This demo showcases visualization and analysis (heavy statistics) for forecasting energy usage based on historical data. We have access to hour-by-hour utility usage for the month of

In this example, use a database of 1985 car imports with 205 observations, 25 predictors, and 1 response, which is insurance risk rating, or "symboling." The first 15 variables are numeric

Solve the wave equation using command-line functions. It solves the equation with boundary conditions u = 0 at the left and right sides, and at the top and bottom. The initial conditions are

Use the fit function to fit polynomials to data. The steps fit and plot polynomial curves and a surface, specify fit options, return goodness of fit statistics, calculate predictions, and

Demonstrates fitting a non-linear temperature model to hourly dry bulb temperatures recorded in the New England region. The temperature series is modeled as a sum of two compoments, a

Rare events prediction in complex technical systems has been very interesting and critical issue for many industrial and commercial fields due to huge increase of sensors and rapid growth

Compute and plot the pdf of a Poisson distribution with parameter lambda = 5.

This examples illustrates how to perform a FORM analysis on a discrete (0 or 1) failure response. In the example we'll compare a traditional Monte Carlo method with FORM. This example is was

Copyright 2016 The MathWorks, Inc.Published with MATLAB® R2016a

This script demonstrates using the included Talbot and Euler algorithms for numerical approximations of the inverse Laplace transform. The examples cover functions with known inverses

Clustering is a form of unsupervised learning technique. The purpose of clustering is to identify natural groupings of data from a large data set to produce a concise representation based on

Goal - Produce a reliable med term forecasting model for Energy Demand

Most PID tuning rules are based on the assumption that the plant can be approaximated by a first-order plus time delay system. This code explains why this assumption is valid and how to

Dynamic Matrix Control (DMC) was the first Model Predictive Control (MPC) algorithm introduced in early 1980s. Nowadays, DMC is available in almost all commercial industrial distributed

Explores more in-depth interaction with the Gazebo® Simulator from MATLAB®. Topics include creating simple models, adding links and joints to models, connecting models together, and

Illustration of H-infinity loop-shaping with Robust Control Toolbox

Previously, we developed a back testing framework to calibrate a simple trading strategy to intraday data. In this demo we'll use extend the approach to three signals: MA, RSI, and Williams

The following example illustrate the change in peak time, settling time and percent overshoot as the poles of a 2nd order system move horizontaly, vertically and with fixed angle on the

This document explains how to use the setup function and online controller returned by ssmpcsetup.

Use the command line features of anfis on a chaotic time-series prediction example.

A simulink model of Kalman filter organized as a feedback control system

This demo expands on the previous demo to incorporate a larger, intraday trading set (loaded from a database). More data implies more calculations, so we use Parallel Computing Toolbox to

Runs a market maker based upon bayesian updating of the probability of the bid or ask price.

Most PID tuning rules are based on first-order plus time delay assumption of the plant hence cannot ensure the best control performance. Using mordern optimization techniques, it is

This document explains how to use the DMC Simulink block.

Create a flight animation for a trajectory using a FlightGear Animation object.

Implement a steady, viscous flow through an insulated, constant-area duct using the Aerospace Toolbox™ software. This flow is also called Fanno line flow.

This demo shows how functionality within Econometric Toolbox can be used to identify and calibrate a simple, intraday pairs trading strategy.

Visualize aircraft takeoff and chase helicopter with the virtual reality animation object. In this example, you can use the Aero.VirtualRealityAnimation object to set up a virtual

The PID controller is the most widely used controller in various engineering systems. However, appropriately tuning a PID controller is not an easy task althrough it has only three

This demonstration uses the 'ab' example of AUTO to demonstrate the use of the Dynamical Systems Toolbox in the 07P (AUTO) mode. Input and output files are similar to the ones used in AUTO.

This demo is uses MATLAB to develop and test a simple trading strategy using an exponential moving average.

This demonstration uses the 'ab' example of AUTO to demonstrate the use of Matlab functions with the Dynamical Systems Toolbox in the DST mode.

This demo illustrates the computation of a solution family to the boundary value problem

This demonstration uses the 'ab' example of AUTO to demonstrate the use of Simulink with the Dynamical Systems Toolbox in the DST mode.

This examples shows you how to filter an ECG signal that has high-freqquency noise, and remove the noise by low-pass filtering.

Multiple-Input-Multiple-Output (MIMO) systems, which use multiple antennas at the transmitter and receiver ends of a wireless communication system. MIMO systems are increasingly

Simulate a basic communication system in which the signal is first QPSK modulated and then subjected to Orthogonal Frequency Division Multiplexing. The signal is then passed through an

Design lowpass filters. The example highlights some of the most commonly used command-line tools in the DSP System Toolbox. Alternatively, you can use the Filter Builder app to implement

Use the Communications System Toolbox to visualize signal behavior through the use of eye diagrams and scatter plots. The example uses a QPSK signal which is passed through a square-root

How multiple Channel State Information (CSI) processes provide the network with feedback for Coordinated Multipoint (CoMP) operation. In this example User Equipment (UE) data is

Use System objects to do streaming signal processing in MATLAB. The signals are read in and processed frame by frame (or block by block) in each processing loop. You can control the size of each

Implement a speech compression technique known as Linear Prediction Coding (LPC) using DSP System Toolbox™ functionality available at the MATLAB® command line.

Design lowpass FIR filters. Many of the concepts presented here can be extended to other responses such as highpass, bandpass, etc.

Demonstrates how to measure the Channel Quality Indicator (CQI) reporting performance using the LTE System Toolbox™ under conformance test conditions as defined in TS36.101 Section

Compute the time-domain response of a simple bandpass filter:

Use the Complementary Cumulative Distribution Function (CCDF) System object to measure the probability of a signal's instantaneous power being greater than a specified level over its

The example performs Huffman encoding and decoding using a source whose alphabet has three symbols. Notice that the huffmanenco and huffmandeco functions use the dictionary created by

Calculate the cascaded gain, noise figure, and 3rd order intercept (IP3) of a chain of RF stages. Each stage is represented by a frequency independent "black box", specified with it's own

How an over-the-air LTE waveform can be generated and analyzed using the LTE System Toolbox™, the Instrument Control Toolbox™ and an Agilent Technologies® RF signal generator and

Use the Least Mean Square (LMS) algorithm to subtract noise from an input signal. The LMS adaptive filter uses the reference signal on the Input port and the desired signal on the Desired port

Use wavelets to analyze electrocardiogram (ECG) signals. ECG signals are frequently nonstationary meaning that their frequency content changes over time. These changes are the events of

Generate an Enhanced Physical Downlink Control Channel (EPDCCH) transmission using the LTE System Toolbox™.

Provides visualization capabilities to see the effects of RF impairments and corrections in a satellite downlink. The link employs 16-QAM modulation in the presence of AWGN and uses a High

Demonstrates how to measure the Rank Indicator (RI) reporting performance using the LTE System Toolbox™ under conformance test conditions as defined in TS36.101 Section 9.5.1.1 [ 1 ].

A digital communications system using QPSK modulation. The example uses Communications System objects to simulate the QPSK transceiver. In particular, this example illustrates methods

A method for digital communication with OFDM synchronization based upon the IEEE 802.11a standard. System objects from the Communication System Toolbox are utilized to provide OFDM

Use the LTE System Toolbox™ to create a frame worth of data, pass it through a fading channel and perform channel estimation and equalization. Two figures are created illustrating the

If manual comparison by a fingerprint expert is always done to say if two fingerprint images are coming from the same finger in critical cases, automated methods are widely used now.

David Young

In this IoT project, we use a Raspberry Pi, a web cam and ThingSpeak to count cars on a busy highway. We deploy a car-counting algorithm to the Raspberry Pi device, and we analyze and visualize

Uses Lucas-Kanade method on two images and calculate the optical flow vector for moving objects in the image.

Government intelligence agencies need to continually analyze thousands of images of enemy territory. They are always looking for change - for instance, has the enemy relocated any of its

How to use Cell Mode in the MATLAB Editor.

File : haar_featlist

By Jarek Tuszynski

This function interpolates values of a georeferenced tiff file, given lat/lon coordinates or map x/y locations corresponding to the map projection associated with the tiff file. This

Reduces the number of image colors.

The Droste Effect is when an image recursively includes itself. The basic method is to insert a scaled copy of the image, but more interesting results can be acheived via conformal mapping.

A brief introduction to directional lapped orthogonal transforms

Create a South-polar Stereographic Azimuthal projection map extending from the South Pole to 20 degrees S, centered on longitude 150 degrees West. Include a value for the Origin property in

Combines a few built-in Matlab functions with some functions you'll find on the Mathworks File Exchange site.

The filt2 function performs a highpass, lowpass, bandpass, or bandstop 2D gaussian filter on gridded data such as topographic, atmospheric, oceanographic, or any kind of geospatial data.

Url = 'http://ec2-54-187-132-60.us-west-2.compute.amazonaws.com/api?user=anita.gajjala@mathworks.com'; filename = 'data.zip'; websave(filename,url); unzip(filename);

We'd like to read in locations of recent earthquakes from USGS website and plot them on an interactive map.

The ramp function plots the Radarsat Antarctic Mapping Project version 2 using Antarctic Mapping Tools for Matlab. RAMP data are described in full on the NSIDC website. If you use RAMP data,

Demonstrates the use of a Bitalino to acquire data into MATLAB and to process the raw ADC data to measure heart rate and to visualize some ECG measurements.

KPIB is a framework for operating laboratory instruments that are connected to a computer by GPIB or serial port connections. KPIB provides a unified interface for communicating with

Reads the value from the specified analog pin. Returns analog pins state as a n x 2 array, representing KEY-VALUE pairs of digital pins. The Engduino board contains a 5 channel 10-bit analog to

Writes an analog value (PWM wave) to a pin. Can be used to light a LED at varying brightnesses or drive a motor at various speeds. After a call to analogWrite(), the pin will generate a steady

Write a HIGH or a LOW value to a digital pin. If the pin has been configured as an OUTPUT with pinMode(), its voltage will be set to the corresponding value: 5V (or 3.3V on 3.3V boards) for HIGH, 0V

Sphero is not listed under available devices when creating the sphero object, or the following error is received:

This example shows how to generate code from packData and unpackData

How the Sphero Connectivity Package can be used to connect to a Sphero device and perform basic operations on the hardware, such as change the LED color, calibrate the orientation of the robot

Configures the specified pin to behave either as an input or an output. See the description of digital pins for details on the functionality of the pins. It is possible to enable the internal

Control the motion of a Sphero using the Sphero Connectivity Package

This examples shows how to exchange live data with Data Acquisition hardware using simple for or while loops and System object™ interfaces.

Get the temperature value in celcius from Engduino

Pack and unpack data using the provided packData and unpackData functions

Reads the value from the specified digital pin. Returns digital pins state as a n x 2 array, representing KEY-VALUE pairs of digital pins.

Description: This example shows Engduino 'analogRead' function call. Function returns values of the analog pin.

Set individual colours and brightness for all 16 LEDs on Engduino

Import Java robot for keyboard control. This Java class is not officially supported by Matlab. Please refer to Java website for more information on this class

Set individual colours of all the 16 LEDs on Engduino

Set status settings

Returns requested status parameters

Description: This example shows calibration of Engduino's magnetometer. Because the measured magnetic field is a combination of both the earth's magnetic field and any magnetic field

Get the xyz value of accelerometer on Engduino

Description: This example shows Engduino Sensors 'getAccelerometer' function call. Function returns acceleration in [x,y,z] directions. Unit is [G=10m/s^2]

This demo is an introduction to using MATLAB to develop and test a simple trading strategy using an exponential moving average.

This script will demonstrate some simple examples related to creating, routing and managing orders from MATLAB via Bloomberg EMSX.

Will be removed in a future release.

This demo uses MATLAB and the Technical Analysis (TA) Developer Toolbox to create and test a pairs trading strategy. The TA Developer toolbox complements the existing computational

This demo extends work done in AlgoTradingDemo1.m and adds an RSI technical indicator to the mix. Copyright 2010, The MathWorks, Inc. All rights reserved.

Copyright 2017 The MathWorks, Inc.

Demonstrates calibrating an Ornstein-Uhlenbeck mean reverting stochastic model from historical data of natural gas prices. The model is then used to simulate the spot prices into the

Inspect a squared residual series for autocorrelation by plotting the sample autocorrelation function (ACF) and partial autocorrelation function (PACF). Then, conduct a Ljung-Box

In AlgoTradingDemo3.m we saw how to add two signals together to get improved results using evolutionary learning. In this demo we'll use extend the approach to three signals: MA, RSI, and

In AlgoTradingDemo2.m we saw how to add two signals together to get improved results. In this demo we'll use evolutionary learning (genetic algorithm) to select our signals and the logic

DISCLAIMER: THE SAMPLE FILES ENCLOSED IN THIS DOWNLOAD ARE FOR ILLUSTRATION PURPOSES ONLY. USE THE INFORMATION CONTAINED IN THIS DOWNLOAD AT YOUR OWN RISK.

Assess whether a time series is a random walk. It uses market data for daily returns of stocks and cash (money market) from the period January 1, 2000 to November 7, 2005.

This demo shows how to price a GMWB rider. Yi Wang, MathWorks, 2010

Copyright 2017-2017 The MathWorks, Inc.

This demo develops and tests a simple exponential moving average trading strategy. It encorporates obtaining data from the Bloomberg BLP datafeed and executing trades in EMSX, based on the

We seek to try out ga and patternsearch functions of the Genetic Algorithm and Direct Search Toolbox. We consider the unconstrained mean-variance portfolio optimization problem, handled

Compute and plot the impulse response function for an autoregressive (AR) model. The AR(p) model is given by

Demonstrates optimizing a storage facility and valuing a storage contract using intrinsic valuation. The optimization involves finding the optimal positions in a set of forward natural

This demo uses our simple intraday moving average strategy to develop a trading system. Based on historical and current data, the decision engine decides whether or not to trade, and sends

To illustrate assigning property values, consider specifying the AR(2) model

Several ways of visualizing the results of functional metagenomic analyses. The discussion is based on two studies focusing on the metagenomic analysis of the human distal gut microbiome.

Retrieve gene expression data series (GSE) from the NCBI Gene Expression Omnibus (GEO) and perform basic analysis on the expression profiles.

Programmatically search and retrieve data from NCBI's Entrez databases using NCBI's Entrez Utilities (E-Utilities).

A number of ways to look for patterns in gene expression profiles.

Analyze Illumina BeadChip gene expression summary data using MATLAB® and Bioinformatics Toolbox™ functions.

Construct phylogenetic trees from mtDNA sequences for the Hominidae taxa (also known as pongidae). This family embraces the gorillas, chimpanzees, orangutans and humans.

A secondary structure prediction method that uses a feed-forward neural network and the functionality available with the Neural Network Toolbox™.

Use the Global Optimization Toolbox with the Bioinformatics Toolbox™ to optimize the search for features to classify mass spectrometry (SELDI) data.

Classify mass spectrometry data and shows some statistical tools that can be used to look for potential disease markers and proteomic pattern diagnostics.

Identify differentially expressed genes from microarray data and uses Gene Ontology to determine significant biological functions that are associated to the down- and up-regulated

Illustrates how to use the rnafold and rnaplot functions to predict and plot the secondary structure of an RNA sequence.

Test RNA-Seq data for differentially expressed genes using a negative binomial model.

How Bioinformatics Toolbox™ can be used to work with and vizualize graphs.

Various ways to explore and visualize raw microarray data. The example uses microarray data from a study of gene expression in mouse brains [1].

Calculate Ka/Ks ratios for eight genes in the H5N1 and H2N3 virus genomes, and perform a phylogenetic analysis on the HA gene from H5N1 virus isolated from chickens across Africa and Asia. For

Improve the quality of raw mass spectrometry data. In particular, this example illustrates the typical steps for preprocesssing protein surface-enhanced laser

How HMM profiles are used to characterize protein families. Profile analysis is a key tool in bioinformatics. The common pairwise comparison methods are usually not sensitive and specific

Workflows for the analysis of gene expression data with the attractor metagene algorithm. Gene expression data is available for many model organisms and disease conditions. This example

Use MATLAB® and Bioinformatics Toolbox™ for preprocessing Affymetrix® oligonucleotide microarray probe-level data with two preprocessing techniques, Robust Multi-array Average

Illustrates a simple metagenomic analysis on a sample data set from the Sargasso Sea. It requires the taxonomy information included in the files gi_taxid_prot.dmp, names.dmp and

Manipulate, preprocess and visualize data from Liquid Chromatography coupled with Mass Spectrometry (LC/MS). These large and high dimensional data sets are extensively utilized in

Illustrates a simple approach to searching for potential regulatory motifs in a set of co-expressed genomic sequences by identifying significantly over-represented ungapped words of

Enrich microarray gene expression data using the Gene Ontology relationships.

Generate a standalone C library from MATLAB code that implements a simple Sobel filter that performs edge detection on images. The example also shows how to generate and test a MEX function in

The recommended workflow for generating C code from a MATLAB function using the 'codegen' command. These are the steps: 1. Add the %#codegen directive to the MATLAB function to indicate that

Generate C code for a MATLAB Kalman filter function,'kalmanfilter', which estimates the position of a moving object based on past noisy measurements. It also shows how to generate a MEX

Generate HDL code from a MATLAB® design that does image enhancement using histogram equalization.

Use the HDL Coder™ to generate a custom HDL IP core which blinks LEDs on the Arrow® SoCKit® evaluation kit, and shows how to use Embedded Coder® to generate C code that runs on the ARM® processor

Compute square root using a CORDIC kernel algorithm in MATLAB®. CORDIC-based algorithms are critical to many embedded applications, including motor controls, navigation, signal

Generate a standalone C library from MATLAB code that reads a file from disk using the standard C functions fopen/fread/fclose. To call these C functions, the MATLAB code uses the

Model, prototype, tune, and deploy algorithms using Simulink® and Embedded Coder® with the STM32F4 Discovery board. The audio filter tuning example demonstrates this workflow.

HDL code generation from a floating-point MATLAB® design that is not ready for code generation in two steps. First we use float2fixed conversion process to generate a lookup table based

Generate HDL code from a MATLAB® design that implements an LMS filter. It also shows how to design a testbench that implements noise cancellation using this filter.

Use MATLAB® HDL Workflow Advisor to generate a custom HDL IP core which blinks LEDs on FPGA board. The generated IP core can be used on Xilinx® Zynq® platform, or on any Xilinx FPGA with

Generate a MEX function from a simple MATLAB function using the 'codegen' command. You can use 'codegen' to check that your MATLAB code is suitable for code generation and, in many cases, to

Generate HDL code from a MATLAB® design implementing the adaptive median filter algorithm suited for HDL code generation.

Generate HDL code from MATLAB® design implementing an bisection algorithm to calculate the square root of a number in fixed point notation.

This demo shows how a fixed-point cordic algorithm to calculate a phase from polar coordinates (arctan) can be implemented in MATLAB.

Convert a textbook version of the Fast Fourier Transform (FFT) algorithm into fixed-point MATLAB® code.

Use the HDL Coder™ to generate a custom HDL IP core which blinks LEDs on the Xilinx® Zynq® ZC702 evaluation kit, and shows how to use Embedded Coder® to generate C code that runs on the ARM®

Use the CORDIC algorithm, polynomial approximation, and lookup table approaches to calculate the fixed-point, four quadrant inverse tangent. These implementations are approximations

Use both CORDIC-based and lookup table-based algorithms provided by the Fixed-Point Designer™ to approximate the MATLAB® sine (SIN) and cosine (COS) functions. Efficient fixed-point

Demonstrates building and validating a short term electricity load forecasting model with MATLAB. The models take into account multiple sources of information including temperatures

Demonstrates building and validating a short term electricity price forecasting model with MATLAB using Neural Networks. The models take into account multiple sources of information

We will be analysing data from a continuous process of electrolytic copper production at Boliden AB (Skelleftehamn, Sweden).

One of the more common trading strategies within the commodities trading community is trend following. Trend following is an absolute momentum strategy in that it assumes that a particular

Another popular form of trading strategy that is often employed by commodities traders and analysts is cross-sectional momentum, which seeks to measure and rank momentum across multiple

Importing data from a variety of sources and aligning / cleaning up the data consumes a significant portion of an analyst workflow. It can be challenging to align and synchronize data from

Demonstrates an alternate model for building relationships between historical weather and load data to build and test a short term load forecasting. The model used is a set of aggregated

It is often a good idea to verify the performance of a backtested trading strategy with a chunk of market data that it has previously not been tested on. At the beginning of this webinar, we had

Ideas for trading strategies can very often be generated by visual exploration of the price data. MATLAB's interactive plotting tools enable analysts to quickly visualize and explore

Once a trading strategy has been identified and refined by the analyst, the next steps in the workflow involve backtesting the strategy and generating multiple analytics to capture

While backtesting a trading strategy, the analyst is often required to determine the optimal values of various strategy parameters and measure the sensitivity of the strategy's profits to

Illustrates how to set the width of the page margins of a Microsoft Word report.

Illustrates a functional approach to creating a report generator based on the DOM API. It uses the DOM API to create a MATLAB function, rptmagic, that generates a PDF, HTML, or a Microsoft Word

Illustrates an object-oriented approach to creating a report generator based on the DOM API. It uses the DOM API to create pair of MATLAB classes, MagicSquareReport and

The DOM API supports, but does not require, use of templates to generate reports. As this example illustrates, you can use the API to create scripts that generate and format content without

The Report Generator's PowerPoint API allows you to create MATLAB applications that present results as Microsoft PowerPoint presentations. This examples shows the use of the API to create

Illustrates a report generator created with the help of the Report Explorer, the Report Generator's interactive report generation program designer. The report generator in this example

Determines the minimum arrival delay using a large set of flight data that is stored in a database.

Determines the mean arrival delay of a large set of flight data that is stored in a database using MapReduce. You can access large data sets using a DatabaseDatastore object with Database

Create a DatabaseDatastore object for accessing collections of data stored in a relational database. After creating a DatabaseDatastore object, you can preview data, read data in chunks,

Move data between MATLAB® and the MATLAB® interface to SQLite. Suppose that you have product data that you want to import into MATLAB®. You can load this data quickly into a SQLite database

Import Boolean data from a database table into the MATLAB® workspace. MATLAB® imports Boolean data from databases into the MATLAB® workspace as data type logical. This data has values of

Traverse a graph and explore its structure using the MATLAB® interface to Neo4j®. For details about the MATLAB® interface to Neo4j®, see docid:database_ug.bveys16-1.

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