998 resultados para Modelos de Volterra
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Tesis (Maestría en Ciencias Agrícolas) UANL, 2011.
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Tesis (Maestría en Ciencias con Orientación en Ingeniería Ambiental) UANL, 2012.
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Tesis (Maestría en Ciencias con Orientación en Ingeniería Estructural) UANL, 2011.
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Tesis (Maestría en Psicología con Orientación en Terapia Breve) UANL, 2012.
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Tesis (Maestría en Ciencias con especialidad en Ingeniería Estructural) UANL, 2014.
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UANL
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UANL
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Tesis ( Doctor en Ingeniería Eléctrica) U.A.N.L.
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[Tesis] ( Doctor en Ciencias con Especialidad en Manejo de Recursos Naturales ) U.A.N.L.
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Tesis (Doctor en Ingeniería Física Industrial) UANL, 2011.
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Tesis (Doctora en Filosofía con Acentuación en Estudios de la Educación) UANL, 2012.
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Tesis (Doctor en Ciencias con orientación en Farmacología y Toxicología) UANL, 2014.
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The paper summarizes the design and implementation of a quadratic edge detection filter, based on Volterra series, for enhancing calcifications in mammograms. The proposed filter can account for much of the polynomial nonlinearities inherent in the input mammogram image and can replace the conventional edge detectors like Laplacian, gaussian etc. The filter gives rise to improved visualization and early detection of microcalcifications, which if left undetected, can lead to breast cancer. The performance of the filter is analyzed and found superior to conventional spatial edge detectors
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The basic concepts of digital signal processing are taught to the students in engineering and science. The focus of the course is on linear, time invariant systems. The question as to what happens when the system is governed by a quadratic or cubic equation remains unanswered in the vast majority of literature on signal processing. Light has been shed on this problem when John V Mathews and Giovanni L Sicuranza published the book Polynomial Signal Processing. This book opened up an unseen vista of polynomial systems for signal and image processing. The book presented the theory and implementations of both adaptive and non-adaptive FIR and IIR quadratic systems which offer improved performance than conventional linear systems. The theory of quadratic systems presents a pristine and virgin area of research that offers computationally intensive work. Once the area of research is selected, the next issue is the choice of the software tool to carry out the work. Conventional languages like C and C++ are easily eliminated as they are not interpreted and lack good quality plotting libraries. MATLAB is proved to be very slow and so do SCILAB and Octave. The search for a language for scientific computing that was as fast as C, but with a good quality plotting library, ended up in Python, a distant relative of LISP. It proved to be ideal for scientific computing. An account of the use of Python, its scientific computing package scipy and the plotting library pylab is given in the appendix Initially, work is focused on designing predictors that exploit the polynomial nonlinearities inherent in speech generation mechanisms. Soon, the work got diverted into medical image processing which offered more potential to exploit by the use of quadratic methods. The major focus in this area is on quadratic edge detection methods for retinal images and fingerprints as well as de-noising raw MRI signals
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