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In this paper we present a web-based tutoring system designed to enhance a student's conceptual understanding by providing many concept-centered exercises. The system relies on a course textbook from an introductory Signal Processing course for knowledge representation, and also on a large database of relevant problems. We construct concept maps from the textbook to create meta-data for various textbook...
Digital filters with adjustable bandwidths controlled by one or two parameters are desirable in many applications. This paper treats the design and implementation of linear phase Finite Impulse Response (FIR) adjustable bandwidth filters using the Farrow structure which employs several basis filters in parallel. The complete development process from basis-filter design optimization to FPGA hardware...
Filterbank implementations and simulations can be used successfully in introductory signal processing lab courses by avoiding some of the analytical complexities and focusing on real-world applications. One excellent area is human hearing where the cochlea is well modelled by a filterbank. A lab project that simulates a cochlear implant (CI) combines elements of signal processing with biomedical engineering...
This paper deals with location estimation in the presence of unreliable measurements (outliers) in large scale geolocation systems. In order to find a way of identifying these outliers, we propose an adaptive RANSAC (Random Sample Consensus) algorithm that maintains a consensus set which iteratively includes inliers and rejects outliers. Numerical experiments are performed to apply the proposed algorithm...
We address vehicle classification and mensuration problems using acoustic and video sensors. In this paper, we show how to estimate a vehicle's speed, width, and length by jointly estimating its acoustic wave-pattern using a single passive acoustic sensor that records the vehicle's drive-by noise. The acoustic wave-pattern is approximated using three envelope shape (ES) components, which approximate...
In this paper, we show how an underlying system’s state vector distribution can be determined in a distributed heterogeneous sensor network with reduced subspace observability at the individual nodes. The presented algorithm can generate the initial state vector distribution for networks with a variety of sensor types as long as the collective set of measurements from all the sensors provides full...
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