Dimitrov, Vassil S.Gomes Coelho, Diego Felipe2018-04-172018-04-172018-04-12Coelho, D. F. G. (2018). Advanced Methods for Efficient Digital Signal Processing and Matrix-Based Computations (Doctoral thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca. doi:10.11575/PRISM/31793http://hdl.handle.net/1880/106505Modern engineering and scientific problems demand a great amount of data processing power. The type of data that needs to be processed varies from application to application. Image processing, genome matching, physics phenomena simulation, and cryptography are a few examples of processing-power demanding applications. In a wide range of those computationally intensive applications, the arithmetic complexity plays an important role, having direct impact on the implementation performance. In this thesis, we present several methods that are novel contributions of the author to some computationally intensive problems. The introduced methods reduce the overall computing time or other relevant hardware’ and software implementation metrics by decreasing the arithmetic complexity associated with each task. Verified results are shown with peer-reviewed journal papers in reputable journals. In particular, problems on signal processing, eigenvalue computation, and matrix inversion for radar image classification are considered.engUniversity of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.Fast AlgorithmsDigital Signal ProcessingMatrix ComputationEngineering--Electronics and Electricaldoctoral thesis10.11575/PRISM/31793