MATLAB and FPGA‐based interactive tool for exploring concepts on compressed sensing

Neuromorphic engineering is a discipline used to develop hardware, which can mimic the characteristics and abilities of biological systems by investigating their physiological structures and data transfer mechanisms. The recent studies about the neuromorphic systems mostly consist of robotic applications whose designs are inspired by Central Pattern Generators (CPGs). CPGs are special neural networks which can produce coordinated rhythmic activity patterns and these rhythmic movements are modeled mathematically, tested with simulation programs and verified by hardware implementations. A reconfigurable hardware platform (Field Programmable Gate Array “FPGA”) is compatible with numerical simulation tools, allows software control over hardware, has a user‐friendly interface and allows real time modifications. Thus, recently, it is preferred in CPG based robotic applications. In this study, the details of the modeling, simulation and implementation stages of several CPG structures are introduced by using a digital reconfigurable hardware platform. In order to show the conceptual learning achievements of these stages and to assess the contribution to the modeling, simulation and implementation skills of the students, a training course has been planned for the undergraduate students at Erciyes University. This process has been held in an educative manner supported by a survey and an experimental examination, so that this training course has been evaluated by the trainees in terms of the advantage, practicality, and challenge.

Section: The Modeling Simulation and Implementation Stages Of The Cmentioning

confidence: 99%

Section: The Training Course Detailsmentioning

confidence: 99%

Modeling, simulation, and implementation issues of CPGs for neuromorphic engineering applications

Korkmaz

Öztürk

Kılıç

2018

“…Finally, within the field of real‐time digital signal processing, an educational platform developed to explore some concepts related to the relatively new signal acquisition paradigm, known as compressed sensing, is presented in Ref. . The application described in this study is to be used in graduate and undergraduate courses on digital signal processing at the University of the Americas and the National Institute of Astrophysics, Optics and Electronics in Puebla, Mexico.…”

Section: The Fpga Role In Engineering Educationmentioning

confidence: 99%

Teaching real‐time video processing theory by using an FPGA‐based educational system and the “learning‐by‐doing” method

Guzmán‐Ramírez

García

González

et al. 2017

In the present study, we introduce a FPGA‐based educational system called RELI‐EVA (REconfigurable‐Logic‐based system for Implementation and Evaluation of real‐time Video processing and analysis of Algorithms), which has been integrated into a Computer and Electronic Engineering course by following the “learning‐by‐doing” approach. Therefore, the aim of this system is to provide engineering students with an intuitive tool in order to understand the main algorithms for real‐time video processing and create and test some new algorithms before their real implementation in physical systems. Moreover, with the aim of demonstrating the potential of the developed FPGA‐based system, the development of a practical example for edge detection is presented in order to support the theoretical basis of real‐time video processing. Additionally, a qualitative research method was followed to evaluate the proposed tool. A high percentage of the surveyed students corroborated the success of RELI‐EVA as part of an engineering course. © 2017 Wiley Periodicals, Inc. Comput Appl Eng Educ 25:376–391, 2017; View this article online at http://www.wileyonlinelibrary.com/journal/cae; DOI

A FPGA‐based experimentation system for designing, implementing, and evaluating real‐time video processing and analysis algorithms at undergraduate level

García

Guzmán‐Ramírez

2018

Real‐time digital video processing is an important area for students on computer and electronic engineering courses who have to learn how to design efficient applications required for industry, such as autonomous navigation, automatic detection and recognition of objects, autonomous process supervision, etc. Nevertheless, the computational complexity and large amount of data access within real‐time video processing have resulted in the need for alternative learning environments that facilitate this task. This paper aims to introduce a FPGA‐based system into traditional classrooms to promote experimentation when designing, implementing, and evaluating real‐time video processing and analysis algorithms at undergraduate level. With the aim of evaluating the system proposed in this paper, fourth‐year Computer and Electronic Engineering students performed various real‐time video processing and analysis experiments to effectively design robust algorithms. A qualitative research method identified positive student perceptions that might lead to improved technical skills.