Current Issue : April-June Volume : 2026 Issue Number : 2 Articles : 5 Articles
Ambipolar materials integrating both p-type and n-type charge transport in Electrolyte-Gated transistors (EGTs) are attractive for simplification of circuit design and power reduction. They are demonstrated as promising candidates for the development of advanced computing systems and sensors. However, the investigation of ambipolar materials for signal processing is still largely unexplored. Among ambipolar materials, reduced graphene oxide (rGO) is shown to be suitable for EGTs, due to its high conductivity (conductivity > 1000 S cm−1) and its processability starting from aqueous graphene oxide dispersions. This work presents ambipolar rGO-EGTs that autonomously perform mathematical operations on oscillatory input signals: phase reversal, full- and half-wave rectification, band-stop and high-pass filtering, according to the operating EGT gate voltage. These results prompt rGO-EGTs as embedded building blocks for in situ real time analog signal processing....
To build robust condition monitoring solutions, it is important to identify signals that capture relevant information. However, how a degradation affects a given part of machinery might not be clear at the beginning. As a result, exploration measurement campaigns collecting large amounts of data are needed for initial evaluation. Vibration signals are typical examples of such data. Although, for explorative measurement campaigns, the battery-powered wireless node brings extra flexibility in terms of positioning the sensor at the desired location and facilitates retrofitting, the limited energy posed by them is the major downside. Sending high-sampled data over wireless channels is costly energy-wise if all samples are to be sent. When multiple sensor nodes transmit real-time measurement data concurrently over a wireless channel, the risk of channel saturation increases significantly. Avoiding this requires identifying an optimal balance between sampling time, transmission duration, and payload size. This can be done by processing and compressing data before transmission, on the sensor node close to the data acquisition and later reconstructing the received samples on the central node. In this paper, we analyze two compression mechanisms to ensure a good compression ratio and still allow good signal reconstruction for later analysis. We study two approaches, one based on the Fast Fourier Transform and one on Singular Value Decomposition, and discuss the pros and cons of each variant....
We present techniques for estimating key parameters of OneWeb’s Ku-band downlink signal (10.7–12.7 GHz) and reveal it as a single-carrier QPSK signal with a 230.4 MHz symbol rate. The techniques also estimate the signal’s roll-off factor and center frequencies. Wefurther provide the first published account of OneWeb signal demodulation, revealing the basic frame structure of the downlink signal, including a synchronization sequence that repeats every millisecond and is common across all beams, channels, and satellites. Identifying this sequence enables making time-of-arrival measurements from OneWeb signals. These findings contribute to the growing body of research focused on repurposing low-Earth-orbit satellite communication signals for positioning, navigation, and timing....
A key objective in the development of integrated photonic circuits for large-scale optical quantum information processing is achieving both reconfigurability and stable output signals. One outcome of this development is the creation of multimode photonic processors, or reconfigurable multimode interferometers, which have broad applications in both quantum and classical information processing. However, active cooling systems introduce phase fluctuations in multi-port input signals, leading to instability in interference patterns and degrading signal processing precision. In this work, we implement an on-chip feedback control to mitigate input signal phase fluctuation. This approach reduces phase instability by more than 10-fold for multi-port input signals. This significantly enhances the precision and reliability of signal processing within the photonic processor. To validate the stability and repeatability of matrix multiplication using a feedback control scheme on a photonic processor, we successfully implemented Hadamard transformations of different orders with multi-port input signals....
This paper explores the history of evolving teaching techniques in Digital Signal and Image Processing (DSIP) education with a focus on integrating Artificial Intelligence (AI) tools to close the continuing gap between theory and practice. Since DSIP has been at the center of Telecommunication, Medical Imaging, Robotics and AI, this paper examines active and student-centered learning paradigms, like collaborative, situation-based, and project-based learning (PBL) as viable pedagogical methods. The research methodology includes analyzing a survey using Data Visualization Tools in Python-3.12, 2023. This paper overviews the application of digital tools including MATLAB-R2024a, Python, Cloud-based systems, and AI-based learning analytics to promote experiential and adaptive learning to enable students to test complex signal and image processing systems. The findings emphasize the fact that these practices contribute to developing conceptual knowledge, critical thinking, and solving problems through engaging learners in real-life and datadriven scenarios. The results also indicate how the teachers can upgrade their instructional approach to technological innovations in teaching. Finally, this paper highlights the nature of AI-enriched pedagogies and practical experience to build the skills needed to operate in a more data-intensive, technologically advanced and sustainable engineering environment....
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