AmeriranikistanProject OverviewSynopsisSystem Block DiagramHardwareSelf Organizing Map (SOM)SoftwareMatlab DemoSystem SetupDivision of LaborTimelineCost EstimateRisk analysisSafeguards against risksPossible ImprovementsApplicationsReferences¿Questions?AmeriranikistanAmeriranikistanMuhammad AhmadKyle HustonFarhad MajdeteimouriDan MackinProject OverviewProject Overview•Uses Self Organizing Maps to Model Fiber Optic Cables in Matlab.•Speckle Pattern is recorded in your typical webcam and then passed into Matlab.•We will use the Image Acquisition Toolbox, in Matlab, to analyze the speckle pattern.•The speckle pattern will change as the user taps on the fiber strand in various locations.•The Self-Organizing Map algorithm will learn the topology of the fiber.SynopsisSynopsisLaser light is shone through an optical fiberCamera (CCD) receives the light on the other endUser taps random points on the fiberAlgorithm gradually learns to make a map of the fiberDisplay shows the location of all touches going forwardSystem Block DiagramSystem Block DiagramLaser Multi-Mode Fiber CameraAlgorithmDisplayHardwareSoftwareUSBHardwareHardwareOptical BreadboardRed Laser DiodeFocusing and Collimating LensesMirrorsMulti-Mode FiberCamera (USB Web Cam or CCD Sensor)Personal ComputerSelf Organizing Map (SOM)Self Organizing Map (SOM)Unsupervised Artificial Neural Network (ANN) AlgorithmPattern RecognitionCluster the Distribution of the Input SpaceReduce the dimensionality and visualize high dimensional data preserving the most significant featuresExtract the underlying topology in the input (signal) spaceSoftwareSoftwareMatlab is our choice of software:–SOM is based on linear algebra–Efficient matrix and vector computations–Easy creation of scientific and engineering graphics–Extensibility (Tool Boxes)–I/O functionsMatlab DemoMatlab DemoSystem SetupSystem SetupDivision of LaborDivision of LaborHardware/Calibration – Kyle, DanImage Processing – Muhammad, FarhadSOM Algorithm – Farhad, KyleDisplay Routines – Dan, MuhammadTimelineTimelineID Task Name Duration Start Finish1 PDR 9 day s Fri 8/31/07 Tue 9/11/072 CDR 23 day s Tue 9/11/07 Thu 10/11/073 Milestone 1 16 day s Thu 10/11/07 Thu 11/1/074 Milestone 2 21 day s Thu 11/1/07 Thu 11/29/075 Expo 10 day s Sat 12/1/07 Thu 12/13/076 Hardware Setup 6 day s Mon 9/10/07 Mon 9/17/077 Image Acquisition 6 day s Mon 9/17/07 Mon 9/24/078 Front End Image Processing 9 day s Wed 9/19/07 Mon 10/1/079 SOM Algorithm Dev elopment 34 day s Mon 9/17/07 Thu 11/1/0710 Display 30 day s Mon 10/1/07 Fri 11/9/0711 Integration 40 day s Thu 10/11/07 Tue 12/4/0712 Testing 54 day s Mon 10/1/07 Wed 12/12/0713 Users Manual 69 day s Sat 9/8/07 Tue 12/11/0714 Technical Manual 70 day s Sat 9/8/07 Wed 12/12/07PDRCDRMilestone 1Milestone 2ExpoHardwarImage AFront End ImaSOM Algorithm DevelopmentDisplayIntegrationTestingUsers ManualTechnical Manual8/19 8/26 9/2 9/9 9/16 9/23 9/30 10/7 10/14 10/21 10/28 11/4 11/11 11/18 11/25 12/2 12/9 12/16September October Nov ember DecemberCost EstimateCost EstimateOptical Breadboard $700Red Laser Diode $20Focusing and collimating lenses $20Multi-Mode Fiber $30Camera (USB Web Cam) $80Personal Computer N/ATotal $850Risk analysisRisk analysisThe experimental nature of SOM could lead to delays in the project timelineAny learning curve for the Matlab Image Acquisition ToolboxRunning the algorithm using a scripting language (Matlab) on a best effort OS (Windows) could prove costlyHardware issues (e.g. Fiber breakage and calibration issues)Safeguards against risksSafeguards against risksEarly Integration and TestingPrototyping the SOM AlgorithmPossible Improvements Possible Improvements Automated fiber tapping mechanism for training the SOM algorithmOptimizing the SOMApplicationsApplicationsUsing multiple fibers to model the behavior of flexible structures in spaceAnimation development without any sensor dependenciesReferencesReferencesSelf-Organizing Maps by T. KohonenProfessor Dana Anderson in the physics