Data Analysis with MATLAB Dr. Frank Graeber MathWorks Germany

Transcription

1 Data Analysis with MATLAB Dr. Frank Graeber MathWorks Germany 2014 The MathWorks, Inc. 1

2 Technical Computing Workflow Access Files Data Explore & Create Data Analysis Surface fitting Share Reports and Report Documentation Software Hardware Equations Equations Algorithm Development Derivation & solving x Mathematical Modeling E = Optimization V R Application Development y Report Application Applications Outputs for Design Application F = ma 2

3 Application Areas Technical Computing Signal Processing and Communications Computational Biology Test and Measurement Image Processing Computational Finance Control System Design and Analysis 3

4 Key Industries Aerospace and defense Automotive Biotech and pharmaceutical Communications Education Electronics and semiconductors Energy production Financial services Industrial automation and machinery Medical devices 4

5 The Voices of MATLAB Users 5

6 Black Tusk Geophysics Detects and Classifies Unexploded Ordnance 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% Link to user story Data collection with an advanced metal detector. 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 6

7 NASA Langley Research Center Accelerates Acoustic Data Analysis with GPU Computing 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 Link to user story Wind tunnel test setup featuring the Hybrid Wing Body model (inverted), with 97-microphone phased array (top) and microphone tower (left). 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 7

8 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 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. 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 8

9 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 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 Link to user story 9

10 isonea Develops Mobile App and Server Software for Wheeze Detection and Asthma Management 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 Link to user story The AirSonea device, which connects to an asthma patient s smartphone and communicates with wheeze analysis algorithms on isonea s server. MATLAB enables us to rapidly develop, debug, and test soundprocessing 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 10

11 VivaQuant Accelerates Development and Validation of Embedded Device for Ambulatory ECG Sensing 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 Link to user story ECG snippet before and after processing with VivaQuant s embedded in-band noise removal algorithm. 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 11

12 Chalmers University of Technology Integrates MATLAB Throughout Core Mathematics Curriculum 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 Link to user story Chalmers University in Gothenburg, Sweden. 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 12

13 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 13

14 MathWorks User Story Repository Call for Action: Share Your User Story 14

15 2014 The MathWorks, Inc. 15