Signal Processing Education Research Articles

Design and construction of an in-air sonar for signal processing education

Sonar is an acoustic sensing method commonly used in underwater imaging and navigation. Students are often introduced to sonar theory, but few gain hands-on experience due to the cost and logistical difficulties associated with in-water experimentation. Alternatively, a sonar system can be designed for in-air use to mitigate some of the practical and operational challenges of acquiring sonar field data. Inspired by previous in-air sonar projects, the Pennsylvania State University student chapter of the Acoustical Society of America acquired $5,000 to construct an in-air sonar for exploring signal processing and mechanical design concepts. For a cost-effective solution, consumer audio equipment and additive manufacturing were leveraged. This presentation will walk through the sonar design and build process, discuss the project's current status, and present initial results. Plans for project development and potential inclusion into the curriculum will be discussed. Advice will be offered to those who may want to pursue similar projects.

Teaching Signal Processing with Interactive Tools

In this work we analyze the contents of a typical introductory course on signal processing, discuss the benefit and risks of interactive tools, and present two examples of interactive tools to teach concepts of system identification. Finally, we propose a methodology to develop well documented interactive tools in an efficient way.

Virtual lab design for active filter circuits

Active filter circuits are a crucial topic in electrical, electronics and signal processing education, but their complexity often poses significant challenges to traditional classroom teaching. Virtual labs provide an immersive and interactive learning experience without the need for costly equipment and materials, offering a solution to these challenges. In this research paper, the approach to designing and implementing a virtual laboratory of active filter circuits using JavaScript is presented. The lab includes a breadboard, function generator, multi-meter, and uses a simulation engine to calculate voltage and frequency values in circuits. The virtual lab was evaluated through user research with engineering and science students, and it was found to be highly effective in teaching active filter circuits. Virtual labs are an essential tool in engineering education, providing increased flexibility and reduced costs.

Educational trends in biomedical signal processing

Abstract Biomedical Engineering programs are present at many universities all over the world with an increasing trend. New generations of biomedical engineers have to face the challenges of health care systems round the world which need a large number of professionals not only to support the present technology in the health care system but to develop new devices and services. Biomedical Engineering supports patient diagnosis and treatment by installing, testing, calibrating and repairing biomedical equipment; training users; maintaining safe operations. Also, approves new equipment by conducting tests, ensuring adherence to codes and making modifications. This paper presents a solution for biomedical signal processing education, involving real signal acquisition and computer-based processing. The acquired signals also allow a lot of post processing procedures to be implemented in an educational form/way.

Instruction Tools for Signal Processing and Machine Learning for Ion-Channel Sensors

Ion Channel sensors have several applications including DNA sequencing, biothreat detection, and medical applications. Ion-channel sensors mimic the selective transport mechanism of cell membranes and can detect a wide range of analytes at the molecule level. Analytes are sensed through changes in signal patterns. Papers in the literature have described different methods for ion channel signal analysis. In this paper, we describe a series of new graphical tools for ion channel signal analysis which can be used for research and education. The paper focuses on the utility of this tools in biosensor classes. Teaching signal processing and machine learning for ion channel sensors is challenging because of the multidisciplinary content and student backgrounds which include physics, chemistry, biology and engineering. The paper describes graphical ion channel analysis tools developed for an on-line simulation environment called J-DSP. The tools are integrated and assessed in a graduate bio-sensor course through computer laboratory exercises.

Creativity First, Science Follows: Lessons in Digital Signal Processing Education

Digital signal processing (DSP) education has traditionally employed more demanding mathematics than most topics found among courses in electrical/electronic/computer engineering. In some cases, the technical challenges posed by some courses have made it difficult for students to complete those courses successfully. Here, we advocate for creativity to be nurtured in the first place, after which the science will flow naturally. To foster creativity, our pedagogical approach includes a variety of solutions incorporating exploratory exercises, open-ended multidisciplinary coursework, blended lecture-laboratory sessions, and a colorful working environment. We firmly believe that creativity is the way forward. Student feedback supports our approach.

Teaching Signal Processing Through Frequent and Diverse Design: A Pedagogical Approach

In this article, we describe and discuss the design-based approach for signal processing education at the undergraduate level at the University of New South Wales (UNSW) Sydney. The electrical engineering (EE) undergraduate curriculum at UNSW Sydney includes three dedicated signal processing courses as well as a design course that involves a major signal processing task. Design- and project-based teaching permeate the curriculum and form a primary method of content delivery to not only cement the understanding of theoretical concepts but also strengthen students? ability to apply these concepts to practical problems.

The Transition From White Box to Black Box: Challenges and Opportunities in Signal Processing Education

Modern engineering education is increasingly assuming an interdisciplinary character, where developments in one area almost invariably affect other areas. A prominent example is that of signal processing, which has undergone significant changes with the emergence of machine learning (ML) and deep learning (DL) in recent years. While the impact of ML/DL is clearly visible from the viewpoint of research and development as well as industrial applications, it is not immediately clear how signal processing education should evolve in terms of pedagogy and content. Hence, the main purpose of this article is to provide some insight into this aspect. In particular, we emphasize that the introduction and popularity of ML/DL, especially at the level of teaching, has provided an opportunity to bring the focus back to some of the fundamental ideas rooted in signal processing and other related fields of study.

Research on Digital Signal Processing Experiment System Based on Virtual Instrument Technology

A virtual demonstration experiment system has been designed by using the development environment LabVIEW which is used in digital signal processing teaching in the paper, Nyquist sampling theorem and the relation between circular convolution and linear are introduced in the paper. Teacher could dynamically demonstrate that the variable signal parameters had an effect on experiment phenomenon in these teaching programs. This experiment system has many distinct features such as openness, extension, interaction, digitization, network, modularization, economization, it is both a new way of experimental teaching and a new direction in the experiment teaching innovation, it will powerfully promote the innovation of teaching idea and teaching mode.

SART3D: A MATLAB toolbox for spatial audio and signal processing education

AbstractSignal processing courses form usually a common block within the curriculum of electrical engineering and computer science undergraduate studies. While signal processing is the science behind many technologies used in our everyday life, students usually feel that the practical use of signal processing subjects is obscured due to their intensive theoretical perspective. In this context, audio signal processing is a discipline where many general signal processing concepts can be easily experienced with sound. Specifically, spatial audio, i.e., the manipulation of audio signals with the aim of capturing and/or recreating the spatial impression of sound, provides an excellent and appealing application framework for signal processing education. This paper presents SART3D, an open‐source MATLAB toolbox that facilitates spatial audio and signal processing education by enabling students to focus on the implementation and testing of core algorithms and to experience their own results using real‐time processing. The time required for other nonrelevant aspects, such as hardware and driver set‐up or user interaction, is significantly reduced. Experience evaluated throughout four academic years and 45 students (25% female) indicate they felt particularly engaged when SART3D was included in the course, improving their performance and understanding of the subject. In this context, the four factors defined by the Student Course Engagement Questionnaire (skills, emotional, participation, and performance) were analyzed to assess engagement in its multiple dimensions.

Teaching Digital Signal Processing With a Challenge on Image Forensics [SP Education

With the advent of ubiquitous sensing and real-time data processing, the demand for engineers with solid signal processing skills has exceeded the supply by a large margin. However, even students in technical subjects often perceive signal processing as demanding and somewhat dry [4]. In many curricula, signal processing must compete with more attractive classes, such as hands-on courses on programming, robotics, or computer graphics. Hence, new directions in signal processing education are needed [1], [9], [10].

Study on the Relationship between Students' Mastery of Theory and Practice in Digital Signal Processing Teaching

Digital Signal Processing (Digital Signal Processing, DSP) is a strong theoretical and practical subject, has widely used in many practical fields. Due to lack of knowledge system, it is difficult for students to apply the theory to practice and apply the theory of knowledge to solve practical engineering problems. So in the teaching of Digital Signal Processing, we must take the theory as the guide, take the practice as the center, strengthen the innovation of the teaching mode, and deal with the relationship between theory teaching and practice teaching. In view of the course, we introduce the Fuzzy Cognitive Diagnosis Framework (FuzzyCDF), propose a new teaching effect assessment method. By collecting the theoretical examination and experimental results of students, using the method of data mining fit out test parameter analysis, combining with FuzzyCDF to get master degree of theoretical knowledge and practice ability, then according to the experimental results, give objective and scientific evaluation and provide good advice to improve the quality of teaching.

A Raspberry Pi-Based Platform for Signal Processing Education [SP Education

One of the most important application areas of signal processing (SP) is, without a doubt, the software-defined radio (SDR) field [1]-[3]. Although their introduction dates back to the 1980s, SDRs are now becoming the dominant technology in radio communications, thanks to the dramatic development of SP-optimized programmable hardware, such as field-programmable gate arrays (FPGAs) and digital signal processors (DSPs). Today, the computational throughput of these devices is such that sophisticated SP tasks can be efficiently handled, so that both the baseband and intermediate frequency (IF) sections of current communication systems are usually implemented, according to the SDR paradigm, by the FPGA's reconfigurable circuitry (e.g., [4]-[6]), or by the software running on DSPs.

Teaching Reform Exploration of "Digital Signal Processing" Driven by Engineering Project

A new teaching method is proposed for "Digital signal processing" course for postgraduate students because it is very theoretical and abstract. Digital signal processing teaching reforms consist of the basic theory integration and experiment simulations. The teaching process is driven by engineering project and combined with digital signal processing flow. The classic contents of digital signal processing are deeply analyzed combined with simulations. Algorithms commonly used in engineering are treated as the contents of experiment simulations and complete engineering simulation designs are treated as practice topics. Through this reform practice, postgraduate students will greatly improve in independent study, practice and collaboration and will lay the foundation of their future research work.

Special Article Series on Signal Processing Education via Hands-On and Design Projects [From the Guest Editors

As professionals in the signal and information processing field, we build on the tools and theories we learned in our undergraduate studies, adding knowledge and skills over the years. For many of us, it has been a while since our undergraduate studies, yet we can probably recall some of these “Ahha” moments when a full meaning of some fundamental theory sank in. As educators and mentors, we seize on these moments and our own experiences to implement new successful teaching methods that advance effective learning and skill development.

Modular Integrated Electronic Experiment Testbed for Signal Processing Education

Modular Integrated Electronic Experiment Testbed for Signal Processing Education

Development of MATLAB-Based Digital Signal Processing Teaching Module with Graphical User Interface Environment for Nigerian University

The development of a teaching aid module for digital Signal processing (DSP) in Nigeria Universities was undertaken to address the problem associated with non-availability instructional module. This paper annexes the potential of Peripheral Interface Controllers (PICs) with MATLAB resources to develop a PIC-based system with graphic user interface environment suitable for data acquisition and signal processing. The module accepts data from three different sources: real time acquisition, pre-recorded data acquisition and software-generated data. The developed system is able to perform analysis on both stationary and non-stationary signals using Fast Fourier Transform (FFT) and Short Time Fourier Transform (STFT). The STFT-based approach provides Improved Joint Time Frequency Analysis (IJTFA) of signals. A graphical user interface (GUI) was developed to create interactive environment for understanding the operations of digital signal processing. The developed system not only provides interactive platform for data acquisition, spectral analysis and filter design but also makes it avoidable to students in Nigeria University.

Trends in Signal Processing Education [In the Spotlight

This summary captures the ideas presented in the Trends session on Signal Processing Education (SPED) at ICASSP 2011. In that session, we surveyed a number of key areas of educational innovation and solicited other trends from the audience. While we strive to be as comprehensive as possible, there are quite likely to be gaps in our treatment.

Experiments With Sensor Motes and Java-DSP

Distributed wireless sensor networks (WSNs) are being proposed for various applications including defense, security, and smart stages. The introduction of hardware wireless sensors in a signal processing education setting can serve as a paradigm for data acquisition, collaborative signal processing, or simply as a platform for obtaining, processing, and analyzing real-life real-time data. In this paper, a software interface that enables the Java-digital signal processing (J-DSP) visual programming environment to communicate in a two-way manner with a wireless sensor network is presented. This interface was developed by writing nesC (an extension to the C programming language for sensors) code that enables J-DSP to issue commands to multiple wireless sensor motes, activate specific transducers, and analyze data using any of the existing J-DSP signal processing functions in real time. A series of exercises were developed and disseminated to provide hardware experiences to signals and systems and signal processing undergraduate students. The hardware with the J-DSP software has been used for two semesters in the senior level digital signal processing (DSP) course at Arizona State University. The interface, the exercises, and their assessment (instruments and results) are described in the paper.

Teach-ware: Signal processing resources at connexions [Best of the Web

In this issue, "Best of the Web" presents signal processing education resources available at Connexions (http://cnx.org). Connexions is a platform and environment for scholars to collaboratively develop and rapidly publish educational materials on the Web. It is based on a new approach to education that seeks to provide a place where everyone in the world can freely share knowledge, and it provides equal access to all people via tools that permit everyone ranging from university professors to school children to post and update knowledge in one place.