Using_MATLAB_for_Signal_Analysis.pdf

8/10/2019 Using_MATLAB_for_Signal_Analysis.pdf

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Time Session Title

08:00 Optional Primer: An Overview of MATLAB and the MATLAB Product Family

08:20 Optional Primer: Introduction to Simulink for Modelling and Simulation

08:50 Welcome and Keynote Presentation: MathWorks from Research to Production

09:30 Streamline Your Data Analysis Workflow with MATLAB

10:00 Data Analysis and Modelling with MATLAB: A Practical Approach

10:30 Morning Tea

11:00 Guest Speaker: Industry Case Study

11:30 Model-Based Design Turns 10

12:00Pathways to Production Taking MATLAB and Simulink Algorithms from Research and Design to

Production

12:30 Overviewof Afternoon Sessions

12:35 Lunch

Workshops (held concurrently)

13:30Automatically Converting MATLAB Code to C

CodeData Analysis for Design with MATLAB

14:30Model-Based Design for High-Integrity and

Business-Critical System DevelopmentUsing MATLAB for Signal Analysis

15:40 Closing Remarks, Next Steps, and Q&A

16:00 End

MATLAB Technology Tour 2011 Agenda


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2011 The MathWorks, Inc.

Using MATLAB for Signal Analysis

Daryl NingAppl icat ions Engin eer

MathWorks Aus t ral ia

Level 5, Tower 1

495 Vic tor ia Ave

CHATSWOOD NSW 2067


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Demo: Speech Recognition Application


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Explore & Discover

Technical Computing WorkflowSpeech Recognition Application

Reporting and

Documentation

Outputs for Design

Deployment

Share

Data Analysis

& Modeling

Files

Software

Hardware

Access

Code & Applications

Algorithm

Development

Application

Development

Automate


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Agenda

Explore and Discover

Spectral Estimation

Filter Design

Application Specific Tools

Data Access

Data Acquisition

Communicating with Instruments

System Objects for Streaming Applications

Summary


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Signal Analysis Examples

Physiological Signals

EEG, ECG, EMG

Geophysical signals

Seismic or tidal data

Communications

SDR, RADAR

Images or Video

Medical, Surveillance, Security Audio

Speech, Music


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Explore & Discover

Signal Analysis

& Visualization

Algorithm

Development

Application

Development

Signal transformsfft, dct, czt, hilbert, fwht,

Windowing methodshamming, hann, bartlett, rectwin,

Multirate operationsinterp, decimate,resample,upfirdn,

Spectral estimation algorithmsperiodogram, pwelch, msspectrum,

Statistical signal processingxcorr, xcov, tfestimate, corrmtx,

Explore and DiscoverGeneral Signal Analysis Algorithms


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Explore & Discover

Signal Analysis

& Visualization

Algorithm

Development

Application

Development

FIR Filtersfir1,fir2,fircls,firpm,intfilt,

IIR Filter Design Methods

butter,cheby1,cheby2,ellip,yulewalk,

Adaptive and Multirate Filtersadaptfilt.lms, adaptfilt.rls,

mfilt.firdecim, mfilt.iirdecim,

Filter Analysis and Implementationfvtool,abs,angle,filter,cost,fftfilt,

Specialized Response Typesfdesign.notch,fdesign.octave,

Explore and DiscoverDesign and Implement Digital Filters


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Demo: Remove no ise from a Signal

Band-stop Filter


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Interactive ToolsSPTOOL


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Interactive ToolsFDATOOL*

*Some advanced features requires Filter Design HDL Coder, Fixed Point Toolbox and/or DSP System Toolbox.


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Communications System Toolbox

Image Processing Toolbox

Computer Vision System Toolbox

Phased Array System Toolbox (NEW) RF Toolbox

Wavelet Toolbox


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Ford Motor Company Develops and

Deploys Sound-Quality Metrics with

MATLAB

ChallengeDevelop and deploy sound-quality metrics that correlate

well with subjective impressions of sound

SolutionUse the MATLAB product family to develop a sound

quality analysis tool and deploy SQ metrics to the

company and its worldwide suppliers

Results Improved quality of Ford products

Development time reduced by six months

Source code control

GUI for spark knock detector.

Link to user story
http://www.mathworks.com/company/user_stories/userstory11222.html?by=industryhttp://www.mathworks.com/company/user_stories/userstory11222.html?by=industry


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Argonne National Laboratory Develops

Sensor for Chemical Agent Detection Using

MathWorks Tools

ChallengeDevelop an instrument to reliably detect and identify

gaseous chemicals

SolutionUse MATLAB and related toolboxes to develop a highlysensitive microsensor that can be incorporated into a

wide range of instruments

Results Measurement software code performance

increased by two orders of magnitude Research and development time reduced from one

year to two weeks

SSDK recognized with prestigious award

A scientist needs to focus on

science and shouldnt have to

recreate or debug math libraries

or support code. MathWorkstools are proven, so researchers

can concentrate on new

algorithms and approaches.

Dr. Michael Vogt

Argonne National Laboratory

The Smart Sensor Developer Kit.


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AT4 wireless Increases Internal Test

Coverage to Over 90% for LTE Physical

Layer Test Equipment Designs

ChallengeDevelop test systems for LTE wireless equipment

Solution

Use MATLAB and Simulink to design and simulate theLTE physical layer, verify the FPGA implementation,

and analyze test results

Results Internal test coverage increased to over 90%

Test harness reused throughout the project

life cycle Development effort reduced by 2530%

MATLAB is a universal language that

makes it easy to exchange algorithms

and test results across our team. Our

physical layer model in MATLAB and

Simulink enabled us to better

understand the LTE specifications, and

Model-Based Design enabled us to

verify that our FPGA implementation

conformed to those specifications.

Francisco Javier Campos

AT4 wireless

Link to user story

AT4 wireless LTE layer 1 tester.
http://www.mathworks.com/company/user_stories/userstory20616.html?by=companyhttp://www.mathworks.com/company/user_stories/userstory20616.html?by=companyhttp://www.mathworks.com/company/user_stories/userstory20616.html?by=company


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Institute for Biodiagnostics, Canada

Develops an Imaging Tool for Assessing

Burn Injuries

Images of a first-degree

burn, generated in three

wavelengths from a

spectroscopic camera.

Infrared point

spectroscopy

probe on thetip of a finger.

MathWorks tools allowed us

to thoroughly explore our data,

understand it, and put together

an optimal data analysis

approach.

Dr. Lorenzo Leonardi

Institute for Biognostics, Canada

ChallengeDetermine the severity of burn injuries more quickly and

accurately

SolutionUse MathWorks products to develop a tool to monitor

variations in skin hemodynamics at the site of the wound

Results Effective, noninvasive tool for accessing burns

Flexible test environment

Accelerated algorithm development process


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Automating Digital Filter Implementation

for an Audio Codec at MediaTek

ChallengeDesign audio codec filters to rigorous signal-to-noise ratioand total harmonic distortion standards while minimizing

power consumption and silicon area

SolutionDesign individual filters in MATLAB and Filter Design

Toolbox and use Filter Design HDL Coder to generate

synthesizable RTL code

Results

RTL development cycle reduced from three monthsto less than two weeks

System modifications made in days, not weeks

Evaluation of multiple filter architectures accelerated

Tests of the initial chip run

uncovered no problems

whatsoever with the digital

portion of the audio codec. This

meant that our team was free to

lend a hand with the analog parts

of the design and with the rest of

the testing effort.

MediaTek Inc.

Filter architecture and segment of generated

code.


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SummaryExplore and Discover

MATLAB speeds the development of signal processing

algorithms with built in tools for

Spectral Analysis

Filter Design

Filter Implementation

Extensive documentation and examples to help you get

started

Easy to use GUIs allow you to quickly explore your

data

A high level programming environment allows you to

perform more advanced and customised analysis


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Agenda


Spectral Estimation

Filter Design: FDATOOL and Filterbuilder


Data Access

Data Acquisition



Summary


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Import signals from multimedia files(Audio) .wav, .wma, .aif, .aifc, .aiff, .mp3, .au, .sn

(Video) .qt, .mov, .avi, .asf, .asx, .wmv, .mpg, .mp2, .mp4Files

Software

Instruments/Devices

Access

Code & Applications

Generate standard waveforms in MATLABSine, sawtooth, square, chirp, Gaussian pulse,

Acquire signals from an instrument or deviceSignal analyzers, oscilloscopes, data acquisition boards,

audio sound cards,

Import, Create or Acquire a Signal


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Data Acquisition ToolboxPlug-in data acquisition devices

and sound cards

Instrument Control ToolboxInstruments and RS-232

serial devices

MATLAB

Interfaces for communicating

with everything

Image Acquisition Toolbox

Image capture devices

MATLAB Connects to your Hardware Devices


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Demonstration Setup

Analog Waveform

GPIB Control Commands

Windows Sound

Card (A/D)

Agilent 33120A

Arbitrary Waveform

Generator


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Demonstration Part 1:Working with an Agilent Arbitrary Waveform Generator

set(obj, TriggerSlope, Rising);

fwrite(obj, TRIG:MAI:EDGE:SLO RIS);


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Demonstration Part 2:Acquiring Data with the Data Acquisition Toolbox


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Integrate instruments into

MATLAB applications and

Simulink models

Interactive tool for detecting andcontrolling instruments

Automatic code generation for

faster and easier implementation

Support for IVI, VXIplug&play,

and MATLAB instrument drivers

Support for common

communication protocols

Instrument Control ToolboxControl and communicate with scientific instruments


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GPIB BoardsAgilent Technologies Capital Equipment Corporation (CEC)

CONTEC IOTech

Keithley Measurement ComputingNational Instruments ICS Electronics

VISA Interface (includes Serial, GPIB, VXI, GPIB-VXI, TCP/IP, USB)Agilent National Instruments

Rohde & Schwarz Tektronix

Network ProtocolsTCP/IP and UDP

Serial Port (core functionality in MATLAB)RS-232, RS-422, RS-485Expanded capability with Instrument Control Toolbox

For a full listing, visit: www.mathworks.com/products/instrument

Instrument Control ToolboxCommunication Protocols


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Industry-standard instrument drivers LAN eXtensions for Instrumentation (LXI)

Interchangeable Virtual Instrument (IVI) drivers

VXIplug&play drivers

Several hundred supported instruments Drivers available through the instrument vendor

Instrument drivers do not require knowledge of low-level commands

fwrite(obj, TRIG:MAI:EDGE:SLO RIS);

set(obj, TriggerSlope, Rising);

Instrument Control ToolboxInstrument Drivers


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Vendor Instrument

Driver(IVI or VXIplug&play)

Automatically create MATLAB instrument driver for vendors

driver

Customize MATLAB driver to extend or enhance vendors driver

Create custom MATLAB driver for any instrument

MATLAB instrument drivers available at:

www.mathworks.com/products/instrument/drivers

MATLAB Instrument

Driver

Instrument Control ToolboxInstrument Drivers


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Immediately analyze live or

acquired data in MATLAB and

Simulink

Configure hardware withoutleaving MATLAB

Incorporate custom analysis into

PC-based digital oscilloscope

Ability to do one-shot or

continuous acquisition

Support multiple data acquisition

devices andvendors

Data Acquisition ToolboxAcquire and output data from data acquisition boards


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Acqiris*

ADLINK*

Agilent*

Advantech

CONTEC*

Data Translation*

g.tec*

* Denotes that the hardware manufacturer made the investment to provide this support

For a full support listing, visit: www.mathworks.com.au/products/daq

Any PC compatible sound card (AI, AO)

Parallel Port (DIO)

IOTech*

Keithley

Measurement Computing (MCC)

National Instruments Ono Sokki*

United Electronic Industries*

VXI Technology

Data Acquisition ToolboxSupported Hardware


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Image Acquisition ToolboxAcquire images and video from industry-standard hardware

Stream images and video

directly into MATLAB

Configure device properties Background image acquisition

Live video previewing

Support for multiple hardware

vendors
http://www.mathworks.com/cmsimages/ia_mainimage_wl_4625.jpg


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Image Acquisition ToolboxSupported Hardware

Frame grabbers Matrox Imaging

Data Translation

DALSA Coreco

National Instruments

Digital cameras Hamamatsu

Qimaging

DCAM-compatible cameras (IIDC 1394-based digital camera

specification)

Windows video devices Windows Driver Model (WDM) or Video For Windows (VFW) drivers

Full listing available at www.mathworks.com/products/imaq
http://www.mathworks.com/products/imaqhttp://www.mathworks.com/products/imaq


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The OPCTool GUI enables easybrowsing of a server namespace,

configuring objects, and reading

and writing data.

The OPC Blockset library letsyou communicate data directly

to and from Simulink and your

process system.

OPC ToolboxConnect MATLABAnd Simulink applications to OPC servers.


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Vehicle Network ToolboxSend/Receive CAN packets directly from MATLAB or Simulink

Functions for Tx/Rx of CAN packets

Functions for encoding, decoding,

filtering and logging of CAN messages

Communication blocks for connectinga CAN bus to a Simulink model

Message traffic GUI for visualising live

CAN network traffic

Support for Vector interface hardware

and Vector CAN database (.dbc) files


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Newport Corporation uses MATLAB to validate positional

accuracy of motion control devices used for microchip

fabrication

Software used:

MATLAB

Data AcquisitionToolbox

Instrument Control

Toolbox

Because we use the

Instrument Control and Data

Acquisition Toolboxes, all the

test data is in MATLAB, and

I can obtain the results

immediately . MathWorks

tools saved us hundreds of

hours of testing time.

Reed Farrar

Newport Corporation


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SummaryData Access

MATLAB connects to hardware and instruments

Control instruments directly from MATLAB

Acquire live signals directly into MATLAB

Data access and exploration can be integrated into one

environment

No need to pipeline data between different software

applications

A more streamlined workflow


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Agenda


Spectral Estimation



Data Access

Data Acquisition



Summary


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System objects are MATLAB objects for time-based anddata-driven algorithms, sources, and sinks

System objects make stream processing in MATLAB much

easier

Advantages of system objects over MATLAB functions:

Automatically manage state information

Manage data indexing Implicit data buffering

Introducing System Objects


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Load the entire data set and process it all at once

MATLAB

Signal

Processing

Algorithm

Memory

Data

Files

Batch Processing


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Batch Processing

Requires entire dataset to play audio

Loads entire dataset

into workspace

[audio, Fs] = wavread('dspafxf_8000.wav');

filtCoeff = fir1(40, 0.8,low');

audio_filt = filter(filtCoeff, 1, audio);

wavplay(audio_filt, Fs);


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MATLAB Memory

Stream

Source

Stream Processing

Load a frame of the signal and process it before moving

on to the next frame

Stream

Processing


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Traditional Stream Processing in MATLAB

Explicit state management

Explicit indexing

Need to maintain output buffer

More code than in batch

processing example%% Streaming the MATLAB way% set up initializations

filename = 'dspafxf_8000.wav';

Fs = 8000;

info = mmfileinfo(filename);

num_samples = info.Duration*Fs;

frame_size = 40;

filtCoeff = fir1(40, 0.8,low');filtState = zeros(1,numel(filtCoeff)-1);

output = zeros(1,num_samples);

%% Processing in the loop

index= 1;

while index < (num_samples-frame_size+1)data = wavread(filename,[index index+frame_size-1]);

[datafilt,filtState] = filter(filtCoeff,1,data,filtState);

output(index:index+frame_size-1) = datafilt;

index = index + frame_size;

end

wavplay(output,Fs);


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System Objects Make Stream Processing

Easier

Audio player runs in-the-loop

Implicit states and indexing

In-the-loop code is much simpler

Initialize objects% set up initializations

filename = 'dspafxf_8000.wav';

hAudio = dsp.AudioFileReader(filename, ...

'SamplesPerFrame',40,OutputDataType','double');

hFilt = dsp.DigitalFilter(

TransferFunction, 'FIR (all zeros),

Numerator, fir1(40, 0.8,low');hPlayer = dsp.AudioPlayer('SampleRate', 8000);

%% Processing in the loop

while ~isDone(hAudio)

data = step(hAudio);

datafilt = step(hFilt, data);

step(hPlayer, datafilt);

end


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Demo: Noise Cancellation with an Adaptive

LMS Filter

Adaptivefilter

Z(n) y(n)

d(n)

+

Adapting

algorithm

Clean

signal

d(n)y(n)

Noisy signal

Correlated

to noise

For details, see "Adaptive Filter Theory", 3rd Ed. by S. Haykin, Prentice-Hall 1996.

e(n)

s(n) + z(n)


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Working with System ObjectsExamples from the DSP Systems Toolbox

Signal processing System objects

Eg. Digital filter System object

Create a System object withdefault parameters

Query object parameters and

methods

Example method step:

Use the step method to execute the

algorithm in a loop

dsp.

dsp.DigitalFilter

hFilt = dsp.DigitalFilter

get(hFilt, Property Name)

methods(hFilt)

data_out = step(hFilt, data_in)


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Where Can I Find System Objects?

DSP System Toolbox

Previously the Signal Processing Blockset

Communications System Toolbox

Previously the Communications Toolbox and Communications

Blockset (now combined into a single toolbox)

Computer Vision System Toolbox

Previously the Video and Image Processing Blockset

Phased Array System Toolbox

Brand new to R2011a!


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SummarySystem Objects for Streaming Applications

System Objects make stream processing in MATLAB

much easier

System Objects retain state information

No need to manually track indices and maintain buffers

MATLAB in the loop code becomes simpler

You dont need to be an expert in object oriented

programming to use System Objects


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Agenda


Spectral Estimation



Data Access

Data Acquisition



Summary


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Explore & Discover

Technical Computing Workflow

Reporting and

Documentation

Outputs for Design

Deployment

Share

Data Analysis

& Modeling

Files

Software

Hardware

Access

Code & Applications

Algorithm

Development

Application

Development

Automate


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SummaryUsing MATLAB for Signal Analys is

MATLAB is a powerful environment for design and simulation

of signal processing algorithms

Signal analysis and visualization tools

Signal processing operations and algorithms

Digital filter design and implementation

Interfaces with hardware and instruments

Stream processing techniques with system objects

Application specific tools for Communications, Image/Video

Processing, RF, and Phased Array systems


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Further Information

DSP Application Page:

http://www.mathworks.com.au/dsp/

Technical Literature:

http://www.mathworks.com.au/dsp/technicalliterature.html

MathWorks Australia Pty Ltd Email: [email protected]

Level 5, Tower 1 Phone: 02 8669 4700

495 Victoria Ave Fax: 02 8669 4700

CHATSWOOD NSW 2067 Web: www.mathworks.com.au
http://www.mathworks.com.au/dsp/http://www.mathworks.com.au/dsp/technicalliterature.htmlhttp://www.mathworks.com.au/dsp/technicalliterature.htmlhttp://www.mathworks.com.au/dsp/


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Upcoming Training in Melbourne

http://www.mathworks.com.au/services/training/schedule.html

Jun 22 24 MATLAB Fundamentals

27 MATLAB for Data Processing and Visualisation28 MATLAB Programming Techniques

29 MATLAB for Building Graphical User Interfaces

Aug 2 4 MATLAB Fundamentals

18 19 Signal Processing with MATLAB22 23 Simulink for System and Algorithm Modelling

Interested in an on-site course? Let us know.
http://www.mathworks.com.au/services/training/schedule.htmlhttp://www.mathworks.com.au/services/training/schedule.htmlhttp://www.mathworks.com.au/services/training/schedule.html


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Upcoming Training in Sydney


Jun 21 23 MATLAB Fundamentals for Financial Applications

28 29 Parallel Computing with MATLAB

Jul 20 Interfacing MATLAB with C Code

26 28 MATLAB Fundamentals

Aug 15 16 Signal Processing with MATLAB



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Upcoming Training in Brisbane


Sep 20 MATLAB for Data Processing and Visualisation

21 MATLAB Programming Techniques22 MATLAB for Building Graphical User Interfaces

Oct 25 27 MATLAB Fundamentals



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Upcoming Training in Adelaide


Jun 15 17 MATLAB Fundamentals

Aug 9 10 Simulink for System and Algorithm Modelling

Sep 6 8 MATLAB Fundamentals



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Upcoming Training in Perth


Aug 30 MATLAB for Data Processing and Visualisation

31 MATLAB Programming Techniques

Sep 1 MATLAB for Building Graphical User Interfaces


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