Digital Signal Processing 2: Filtering

Paolo Prandoni is a dedicated lecturer at the École Polytechnique Fédérale de Lausanne (EPFL), where he has been teaching signal processing for over two decades. His passion for the field began during his studies at the University of Padua in Italy, and he furthered his education by obtaining a PhD from EPFL, complemented by a research stint at Berkeley. Throughout his career, Paolo has balanced his academic pursuits with industry experience, working with various start-ups before founding Quividi in Paris, which focuses on innovative solutions in the realm of digital signal processing.At EPFL, Paolo teaches a comprehensive series of courses on digital signal processing, covering fundamental concepts, filtering techniques, and practical applications. His commitment to education and research has made him a prominent figure in the field, where he continues to inspire students and professionals alike to explore the vast possibilities of signal processing technology.

Martin Vetterli is a distinguished professor at the École Polytechnique Fédérale de Lausanne (EPFL), where he has made significant contributions to the field of signal processing. His academic journey includes education at ETH Zurich, Stanford University, and EPFL, and he has previously held faculty positions at Columbia University and the University of California, Berkeley. With a lifelong passion for signal processing, Martin has focused his research on wavelets and filter banks, which are integral to various media standards such as MP3, JPEG, and WiFi. His expertise in these areas has positioned him as a leading figure in the intersection of technology and media.At EPFL, Martin teaches a series of courses on digital signal processing that cover fundamental concepts, filtering techniques, and practical applications. His commitment to education is evident in his engaging teaching style and dedication to mentoring students. Through his work, Martin continues to inspire the next generation of engineers and researchers in the rapidly evolving field of signal processing.