Morgantown, West Virginia
March 24, 2023
March 24, 2023
March 25, 2023
16
10.18260/1-2--44902
https://strategy.asee.org/44902
138
Dr. Mohammed Ferdjallah is an Assistant Professor in the Department of Computer Science & Electrical Engineering at Marshall University. Dr. Mohammed Ferdjallah received his PhD degree in Electrical and Computer and MS degree in Biomedical Engineering from The University of Texas Austin. He also received his MD degree from the International University of the Health Sciences. He has a multidisciplinary expertise in image & signal processing, computational modeling, and statistical data analysis. As an electrical and biomedical engineering scientist, he conducted research in computer modeling of the brain, cranial electrical stimulation (CES), electrical impedance tomography, electrode design, and EMG and muscle action potentials and ions channels simulation & modeling. His technical research interests include digital systems, embedded, systems, computer architecture, adaptive and system identification, modeling and simulation, and signal and image processing. His clinical research interests include impacts of chronic diseases in elderly (such as Alzheimer’s disease, cancer, and diabetes), innovative technology for drug addiction treatment and prevention, medical records, comparative outcomes research, and biomedical sciences. He has successfully published several peer-reviewed articles in biomedical sciences, physical medicine and rehabilitation, modeling and simulation of physiological signals, motion analysis, and engineering.
Since the advent of digital systems, digital filter design has seen an explosion of innovations driven by the ubiquity of microcontrollers and programmable digital systems. Digital filters are not limited by the non-linearities of analog filters and thus are stable and predictable. Traditionally, digital filters design relays on continuous ideal configurations with analytical approximations in the regions of transitions and require mapping using transformation approximations. Additionally, a digital filter will introduce noise during sample/hold, conversion, and quantization. The noise worsens as the filter complexity increases. Furthermore, digital filters introduce a higher fundamental latency that limits their applications to audio and video frequency range.
In this paper, we present a new design procedure that will enhance the versatility of digital filters in optical communications and signal processing. We explore the physical structure of fiber optical filters that takes advantage of the single mode fiber properties and the inherent parallelism of the light. We will examine the optical fibers and their filtering properties in optical signal processing. In particular, we explore the modular structure of fiber optic interferometers for the design of digital filters using the cascade approach. Since the single mode optical fiber has an extremely high bandwidth and very low attenuation transmission medium, a short time-delay bandwidth can be realized. We propose a new approach for designing digital filters based on the single mode optical fiber. The approach demonstrates that a proper nesting or feedback in the optical structure can simplify the filter design. The procedure is a particular case of the theory of low sensitivity discrete time filters structures. Moreover, these digital filters are typical cases where the filters are designed in the z-domain without having the trouble to go through the continuous prototype design. We will implement the new procedure and present simulation design for all-pass and notch digital filters.
Ferdjallah, M. (2023, March), A New Synthesis Procedure for Designing Digital Filters Based on Optical Fiber Structures Paper presented at 2023 ASEE North Central Section Conference, Morgantown, West Virginia. 10.18260/1-2--44902
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