Costa-2015a

PhD thesis

This thesis presents a teaching model for signal reconstruction algorithms and the constraints that are inherent to this engineering problem. For this purpose an application prototype was developed, it was named Signal Processing Interpolation Educational Workbench (SPIEW). The main goal is to improve the students’ learning processes in the signal reconstruction area using a model that approaches the various versed concepts in a graphical and interactive way, from Algebra to Signal Processing, for instance through the application of Error Correction Codes. With SPIEW it is possible to establish conjectures about the signals’ band limiting, error pattern geometries, reconstruction algorithm classes for space dimension signals (maximum) or of the order of the number of lost samples (minimum size), the use of calculation methods: direct, iterative or semi iterative to solve linear equation systems or to measure the optimum computational method’s performance. It is further possible to analyse the stability by verifying if a problem is well/badly conditioned, as well as evaluate the algorithms’ convergence in several scenarios of linear interpolation problems. The data used in this work originating from signals: 1D‐mono audio signals and biotelemetry sensors; 2D‐images including the biomechanic’s area; 3D‐ depth maps using MDC (Multiple Description Coding) 3D video coding; witness the applicability of the proposed methods in various contexts allowing and encouraging the discussion of several real scenarios in the proposed learning environment. The aim of the proposed model, to study signal reconstruction algorithms, isto allow its usersto better understand and increase the concepts inherent to this area of study. By addressing the concepts and operations in a graphical and interactive manner, the user always has the opportunity to view the operations’ results as these are executed step by step, and as such it facilitates the understanding of the more abstract signal processing concepts, even when the user has little knowledge in this area. The developed prototype provides its users with a concrete engineering experience, of a real and actual engineering problem. It allows for the simulation of realistic scenarios of reconstruction problems, giving students the opportunity to test different reconstruction methods and to validate their effectiveness regarding the execution time, and to evaluate the results obtained. In doing so, the engineering systems (projects) for the specific initial requirements can be guaranteed a priori. It was proved, with the realization of Mean Opinion Score (MOS) tests, that the interaction with the users demonstrated it as being an asset in the learning process.