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  • Courseware 
    Signals, Systems and Inference

    Signals, Systems and Inference

    This course covers signals, systems and inference in communication, control and signal processing. Topics include input-output and state-space models of linear systems driven by deterministic and random signals; time- and transform-domain representations in discrete and continuous time; and group delay. State feedback and observers. Probabilistic models; stochastic processes, correlation functions, power spectra, spectral factorization. Least-mean square error estimation; Wiener filtering. Hypothesis testing; detection; matched filters.

    Subjects:
    Electronic and Information Engineering|Electrical Engineering
    Keywords:
    Signal processing Signal theory (Telecommunication) System analysis
    Resource Type:
    Courseware
     
  • Courseware 
    Signals and Systems

    Signals and Systems

    This course covers the fundamentals of signal and system analysis, focusing on representations of discrete-time and continuous-time signals (singularity functions, complex exponentials and geometrics, Fourier representations, Laplace and Z transforms, sampling) and representations of linear, time-invariant systems (difference and differential equations, block diagrams, system functions, poles and zeros, convolution, impulse and step responses, frequency responses). Applications are drawn broadly from engineering and physics, including feedback and control, communications, and signal processing.

    Subjects:
    Electrical Engineering
    Keywords:
    Signal processing System analysis
    Resource Type:
    Courseware
     
  • Presentation 
    Service Science Innovation Lab

    Service Science Innovation Lab

    This video was recorded at COIN / ACTIVE Summer School on Advanced Technologies for Knowledge Intensive Networked Organizations, Aachen 2010. Organized by COIN FP7 Integrated Project (http://www.coin-ip.eu/) and ACTIVE FP7 Integrated Project (http://www.active-project.eu), the summer school seeks to bring together students, scholars and researchers from industry in order to foster collaboration and interoperability through innovative software solutions and share the recent research developments from well-established researchers and educators. The main topics of the summer school are: Interoperability and collaboration models and solutions, Enterprise interoperability and collaboration services, Innovative knowledge and semantically powered technologies, Knowledge process and context modeling, Pro-active knowledge tools, Large scale analytics and reasoning tools, Business cases and real case studies. More about the event at http://coin-active-ss.ijs.si/

    Subjects:
    Management
    Keywords:
    Enterprise application integration (Computer systems) Internetworking (Telecommunication) Management information systems Information resources management
    Resource Type:
    Presentation
     
    OER
  • MOOC 
    Sensor Fusion and Non-linear Filtering for Automotive Systems

    Sensor Fusion and Non-linear Filtering for Automotive Systems

    In this course, we will introduce you to the fundamentals of sensor fusion for automotive systems. Key concepts involve Bayesian statistics and how to recursively estimate parameters of interest using a range of different sensors. The course is designed for students who seek to gain a solid understanding of Bayesian statistics and how to use it to fuse information from different sensors. We emphasize object positioning problems, but the studied techniques are applicable much more generally. The course contains a series of videos, quizzes and hand-on assignments where you get to implement many of the key techniques and build your own sensor fusion toolbox. The course is self-contained, but we highly recommend that you also take the course ChM015x: Multi-target Tracking for Automotive Systems. Together, these courses give you an excellent foundation to tackle advanced problems related to perceiving the traffic situation around an autonomous vehicle using observations from a variety of different sensors, such as, radar, lidar and camera.

    Subjects:
    Electrical Engineering, Mechanical Engineering, and Transportation
    Keywords:
    Automobiles -- Electronic equipment Automotive sensors
    Resource Type:
    MOOC
     
  • Presentation 
    Semantic Web Services Applications

    Semantic Web Services Applications

    This video was recorded at REASE. This is a one-hour video recording of the presentation of John Domingue at the First Asian Autumn School on the Semantic Web. It comprises two videos synchronized with the slides (requires Flash) or the videos alone. Table of Contents: Semantic Web Services: Application Areas Contents DIP DIP Consortium Supporting Emergency Planning for Essex County Council Essex County Council Emergency Planning Context Emergency planning scenario eMerges Ontologies Generic Application Structure Demonstration of Emergency Planning (GIS) Prototype V1 EMerges Prototype Architecture SWS and Business Process Modelling Super Project SUPER Consortium Motivation Querying the Process Space The Critical IT / Process Divide What Are My Services? What are my services? Matching Activities and Port Types Based on Semantics Supporting Business Users Better Matching Model Representations & Semantics The SUPER Stack Modelling Stack Telecommunications Solution Map Content on Demand Digital Rights Management & Content Procurement Modelling Stack Business Process Notations Modelling Stack Programming Model Deploying Applications Business Protocols Modelling Stack WSMO Top Level Notions The SUPER Trinity SUPER Methodology SUPER Architecture SUPER Ontology Stack Super Demo Context Prototype Scenario Digital Asset Management BPMN Service/Process Catalogue Super Demo Video

    Subjects:
    Computing
    Keywords:
    Semantic integration (Computer systems) Semantic Web
    Resource Type:
    Presentation
     
    OER
  • Others 
    Scikit Learn - User Guide

    Scikit Learn - User Guide

    This project was started in 2007 as a Google Summer of Code project by David Cournapeau. Later that year, Matthieu Brucher started work on this project as part of his thesis. In 2010 Fabian Pedregosa, Gael Varoquaux, Alexandre Gramfort and Vincent Michel of INRIA took leadership of the project and made the first public release, February the 1st 2010. Since then, several releases have appeared following a ~ 3-month cycle, and a thriving international community has been leading the development.

    Course related:
    EIE6207 Theoretical Fundamental and Engineering Approaches for Intelligent Signal and Information Processing
    Subjects:
    Computing
    Keywords:
    Machine learning Python (Computer program language)
    Resource Type:
    Others
     
  • Presentation 
    Sampling Table Configurations for the Hierarchical Poisson-Dirichlet Process

    Sampling Table Configurations for the Hierarchical Poisson-Dirichlet Process

    This video was recorded at European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), Athens 2011. Hierarchical modeling and reasoning are fundamental in machine intelligence, and for this the two-parameter Poisson-Dirichlet Process (PDP) plays an important role. The most popular MCMC sampling algorithm for the hierarchical PDP and hierarchical Dirichlet Process is to conduct an incremental sampling based on the Chinese restaurant metaphor, which originates from the Chinese restaurant process (CRP). In this paper, with the same metaphor, we propose a new table representation for the hierarchical PDPs by introducing an auxiliary latent variable, called table indicator, to record which customer takes responsibility for starting a new table. In this way, the new representation allows full exchangeability that is an essential condition for a correct Gibbs sampling algorithm. Based on this representation, we develop a block Gibbs sampling algorithm, which can jointly sample the data item and its table contribution. We test this out on the hierarchical Dirichlet process variant of latent Dirichlet allocation (HDP-LDA) developed by Teh, Jordan, Beal and Blei. Experiment results show that the proposed algorithm outperforms their "posterior sampling by direct assignment" algorithm in both out-of-sample perplexity and convergence speed. The representation can be used with many other hierarchical PDP models.

    Subjects:
    Computing
    Keywords:
    Machine learning Artificial intelligence
    Resource Type:
    Presentation
     
    OER
  • Others 
    SUFR-W (Subtasks of unconstrained face recognition)

    SUFR-W (Subtasks of unconstrained face recognition)

    This package contains: 1. SUFR-W, a dataset of “in the wild” natural images of faces gathered from the internet. The protocol used to create the dataset is described in Leibo, Liao and Poggio (2014) - https://cbmm.mit.edu/publications/conference-abstracts/subtasks-unconstrained-face-recognition 2. The full set of SUFR synthetic datasets, called the “Subtasks of Unconstrained Face Recognition Challenge” in Leibo, Liao and Poggio (2014) - https://cbmm.mit.edu/publications/conference-abstracts/subtasks-unconstrained-face-recognition

    Subjects:
    Computing
    Keywords:
    Human face recognition (Computer science) Optical pattern recognition
    Resource Type:
    Others
     
  • Presentation 
    SEEKDA as IT Multiplier: The Web Services Portal

    SEEKDA as IT Multiplier: The Web Services Portal

    This video was recorded at COIN / PlanetData Winter School on Knowledge Technologies for Complex Business Environments, Ljubljana 2011. Organized by COIN FP7 Integrated Project and PlanetData FP7 Network of Excellence, the school seeks to bring together students, scholars and researchers from industry in order to foster collaboration and interoperability with innovative services and project large-scale data management in business environments. The main topics of the winter school are: Interoperability and collaboration models and solutions, Enterprise interoperability and collaboration services, Innovative knowledge and semantically powered technologies, Knowledge process and context modelling, Pro-active knowledge tools, Large scale analytics and reasoning tools, Business cases and real case studies.

    Subjects:
    Management and Computing
    Keywords:
    Enterprise application integration (Computer systems) Internetworking (Telecommunication) Management information systems Information resources management
    Resource Type:
    Presentation
     
    OER
  • Others 
    Runoob.com

    Runoob.com

    菜鸟教程的 Slogan 为：学的不仅是技术，更是梦想！我们相信：再牛逼的梦想也抵不住傻逼似的坚持！我们坚持一件事情，并不是因为这样做了会有效果，而是坚信，这样做是对的。本站域名为 runoob.com, runoob 为 Running Noob 的缩写，意为：奔跑的菜鸟。本站包括了HTML、CSS、Javascript、PHP、C、Python等各种基础编程教程。同时本站中也提供了大量的在线实例，通过实例，您可以更好地学习如何建站。本站致力于推广各种编程语言技术，所有资源是完全免费的，并且会根据当前互联网的变化实时更新本站内容。

    Subjects:
    Computing
    Keywords:
    Programming languages (Electronic computers) Computer programming
    Resource Type:
    Others