Summary Very powerful framework for estimating parameters of non-linear and non-Gaussian models. Main research directions.
{"Image DocumentName": "SummaryVery powerful framework for estimating parameters of non-linear and non-Gaussian models. Main research directions.", "Image ImageDescription": "Finding new applications for particle filters. Developing variations of particle filters which have reduced complexity. Finding the optimal parameters of the algorithms (number of particles, divergence tests) Challenge. Popularize the particle filter so that it becomes a standard tool for solving many problems in industry. Finding applicactions: applying them to the new applications or increasing complexity and accuracy of the models that are used. 12 Nov SPOT presentation, University of Ottawa, 12 Nov 2004.", "Image XResolution": "37", "Image YResolution": "37", "Image ResolutionUnit": "Pixels/Centimeter", "Image Software": "SlidePlayer", "Image YCbCrPositioning": "Centered"}