1 © 2014 The MathWorks, Inc.

Data Analysis with MATLAB

Dr. Frank Graeber

MathWorks Germany

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Technical Computing Workflow

Equations

Data Surface fitting

Share Access Explore & Create

Derivation & solving

Optimization

Report

Application

Report

Application

Share Access Reports and

Documentation

Outputs for Design

Applications

Explore & Create

Data Analysis Files

Hardware

Software Mathematical Modeling

Algorithm Development

Application Development

x y E = V

R

Equations

F = ma

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Application Areas

Computational Finance

Test and Measurement

Signal Processing and Communications

Control System Design and Analysis

Image Processing

Computational Biology

Technical Computing

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Key Industries

Aerospace and defense

Automotive

Biotech and pharmaceutical

Communications

Education

Electronics and semiconductors

Energy production

Financial services

Industrial automation

and machinery

Medical devices

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The Voices of MATLAB Users

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Challenge Locate buried unexploded ordnance while minimizing the

cost and time expended on unnecessary digging

Solution Use MATLAB to develop and refine algorithms for

detecting and classifying UXO from data acquired by

electromagnetic induction sensors

Results Up to 50% cost savings with 86% reduction in digs

Complex data analyzed and understood

Calculation time cut by almost 75%

Black Tusk Geophysics Detects and

Classifies Unexploded Ordnance

Data collection with an advanced metal detector.

Link to user story

“With MATLAB we have the

ability to optimize algorithms

for nonlinear data fitting and

the flexibility to create user

interfaces that display

complex information in a clear

way. This combination is a

real strength of our solution.”

Laurens Beran

Black Tusk Geophysics

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Challenge Accelerate the analysis of sound recordings from wind

tunnel tests of aircraft components

Solution Use MATLAB and Parallel Computing Toolbox to

re-implement a legacy program for processing acoustic

data, and cut processing time by running

computationally intensive operations on a GPU

Results Computations completed 40 times faster

Algorithm GPU-enabled in 30 minutes

Processing of test data accelerated

NASA Langley Research Center Accelerates

Acoustic Data Analysis with GPU Computing

Wind tunnel test setup featuring the Hybrid Wing

Body model (inverted), with 97-microphone phased

array (top) and microphone tower (left).

Link to user story

“Our legacy code took up to 40

minutes to analyze a single wind

tunnel test; by using MATLAB

and a GPU, computation time is

now under a minute. It took 30

minutes to get our MATLAB

algorithm working on the GPU—

no low-level CUDA programming

was needed.”

Christopher Bahr

NASA

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HKM Optimizes Just-in-Time

Steel Manufacturing Schedule

Challenge Optimize a steel production process to enable

consistent, just-in-time delivery

Solution Use MATLAB and Global Optimization Toolbox to

maximize throughput of more than 5 million tonnes of

steel annually

Results Algorithm development accelerated by a factor of 10

Optimization time cut from 1 hour to 5 minutes

Customer satisfaction increased

“C++, Java, or third-party optimization

solutions would have required us to

spend significantly more time in

development or to simplify our

constraints. Only MATLAB provided

the flexibility, scalability, development

speed, and level of optimization that we

required.”

Alexey Nagaytsev

Hüttenwerke Krupp Mannesmann

Link to user story

Manually reviewed plant schedule (left) and plant schedule

automatically optimized with MATLAB genetic algorithms (right). The

optimized schedule minimizes schedule conflicts (in red), meets

delivery dates, and achieves the target utilization rate.

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Commerzbank Develops Production Software

System for Calculating Derived Market Data

Challenge Compute a variety of derived market data from raw

market data

Solution Use MATLAB to read data from a data management

system in a Windows and Linux architecture, perform

analyses and optimizations, visualize results, and deploy

mission-critical calculations

Results Integration with existing system simplified

Implementation time reduced by months

Updates made in days, not weeks

Link to user story

Commerzbank headquarters in Frankfurt.

“Our solution required a Windows

client and Linux server software. We

used MATLAB to rapidly develop

both by taking advantage of

distributed computing, a MEX-file

interface to access our financial

data, and fast, built-in functions for

optimization, regression, and more.”

Julian Zenglein

Commerzbank

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Challenge Develop and implement an acoustic respiratory

monitoring system for wheeze detection and asthma

management

Solution Develop algorithms for detecting wheeze and ambient

noise in MATLAB, and use MATLAB Coder to generate

code from the algorithms for mobile devices and a web

server

Results Manual coding effort reduced

Algorithm development iterations accelerated

Code maintenance overhead reduced

iSonea Develops Mobile App and Server

Software for Wheeze Detection and

Asthma Management

“MATLAB enables us to rapidly

develop, debug, and test sound-

processing algorithms, and

MATLAB Coder simplifies the

process of implementing those

algorithms in C. There’s no other

environment or programming

language that we could use to

produce similar results in the same

amount of time.”

Mark Mulvey

iSonea

The AirSonea device, which connects to an asthma

patient’s smartphone and communicates with

wheeze analysis algorithms on iSonea’s server.

Link to user story

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Challenge Design and implement an embedded system for extracting

accurate information from noisy electrocardiogram signals

Solution Use MATLAB to develop an algorithm for removing

in-band noise, and use Fixed-Point Designer and

MATLAB Coder to implement it on an ARM Cortex-M

series processor

Results Development accelerated by 300%

Power and memory consumption minimized

Rigorous testing enabled

VivaQuant Accelerates Development and

Validation of Embedded Device for

Ambulatory ECG Sensing

“MATLAB, MATLAB Coder, and

Fixed-Point Designer enabled our

small team to develop a complex

real-time signal processing

algorithm, optimize it to reduce

power and memory requirements,

accelerate embedded code

implementation, and perform the

rigorous testing required for medical

device validation.”

Marina Brockway

VivaQuant

ECG snippet before and after processing with

VivaQuant’s embedded in-band noise removal algorithm.

Link to user story

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Challenge Teach mathematics and mathematical modeling to

students across multiple disciplines and two universities,

and prepare them to meet the needs of industry

Solution Integrate MATLAB throughout the core mathematics

curriculum and provide interdisciplinary exercises in

practical problem-solving

Results Interdepartmental collaboration improved

Students taught skills required by industry

Students self-identified as expert users

Chalmers University of Technology

Integrates MATLAB Throughout Core

Mathematics Curriculum

Chalmers University in Gothenburg, Sweden.

Link to user story

“We train our students to use

MATLAB as an interactive tool not

only for completing the assigned

exercises but also for investigating

mathematical problems and having

fun. We are increasing our focus

on interdisciplinary programs, and

MATLAB is perfect for integrating

mathematics with other subjects.”

Dr. Tommy Gustafsson

Chalmers University of Technology

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Data Analysis with MATLAB Key Takeaways

Accelerate algorithm and application development plus maintenance

Accelerate data processing with parallel or GPU computing

Improve results and your customers’ satisfaction

Accelerate algorithm and application development plus maintenance

Accelerate data processing with parallel or GPU computing

Improve results and your customers’ satisfaction

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15 © 2014 The MathWorks, Inc.