In recent years, the development of deep learning has progressed rapidly, leading to broader applications of neural networks across various domains. These applications are becoming increasingly integrated into our daily lives, such as in mobile …
This paper focuses on the sparse representation direct position determination (SR-DPD) method in motion scenarios with a single station. In contrast to the conventional two-step positioning method, the SR-DPD method eliminates the need to estimate …
Due to the irrational coefficients, the orthogonal wavelet filter banks (FBs) need a lot of resources when implemented on hardware. As a result, there is a decrease in operating speed, a significant memory requirement, and an increase in power …
Cardiovascular diseases (CVDs) are a major public health concern. Electrocardiograms (ECG) are very often used as a tool for CVD diagnosis. Cardiologists scrutinize ECG, searching for signs for diagnosis. Faced with a growing number of patients …
Considering the utilization of the correlation between training data, this paper proposes a graph neural network-based deep learning method for the direction of arrival (DOA) estimation by transforming the DOA estimation problem into a node …
As is well known, Time Difference of Arrival (TDOA) is a technique used for locating the position of a signal source based on the time difference of when the signal arrives at multiple receivers. The iterative method enhances the function through …
Noise extraction from electroencephalogram (EEG) signals has become indispensable in the clinical field. This paper mainly focuses on designing an efficient Hammerstein spline adaptive filter (HSAF) for the ocular noise extraction from the EEG …
The multi-dimensional Special Affine Fourier transform (MSAFT) is an intriguing new addition to the integral transform class, which generalizes several popular unitary transformations, signal processing transformations, and mathematical procedures …
In recent years, image super-resolution (SR) research has made remarkable progress. However, the complexity of the models, such as increased network depth, attention mechanisms, and Transformer structures, has resulted in high computational costs …
The image classification accuracy of convolutional spiking neural network (CSNN) decreases substantially for a distorted image dataset (images with affine transformation). To improve the classification accuracy of CSNN for distorted image dataset …
In array signal processing, some beamforming algorithms require strict prior conditions on the mainlobe width. Therefore, this paper proposes a sparse optimization-based beamforming scheme, namely the minimum mainlobe width algorithm, addressing …
Toom-Cook multiplication algorithm is one of the most efficient method compared to other traditional large-integer multiplication algorithms. However, in most cases, implementation of this algorithm in hardware is practically avoided due to …
In this paper, we elaborate a novel variational model for image denoising, particularly focusing on scenarios with high levels of speckle noise. Our approach integrates fractional-order regularizers to better preserve image edges, overcoming the …
We consider the event-triggered finite-time dissipative control problem for fractional-order interconnected systems with an unknown time-varying delay in the state vector. The controller in this paper uses only information of the state vector when …
In biomedical applications, the data acquisition device for brain activities has gained significant popularity. Numerous brain-acquisition devices have been implemented using various electronic devices. While some devices are sophisticated, the …
The paper suggests a new method for controller design and order reduction of LTI higher-order systems (HOSs). This research uses the model dominance index to determine pole dominance. This metric identifies the dominant poles, even if they are not …
Currently, significant progress has been made in conventional-size image dehazing technology, but restoring ultra-high-definition images is still a challenging task. Existing ultra-high-definition image dehazing methods usually cut down the …
The key requirements for medical implantable devices are low energy consumption and reliable computational precision. In this context, we design a novel filter for ECG signal denoising using the stochastic computing (SC) method. Compared to …
We demonstrate a novel 7.7–12.5 mW, 14.5–24.5 GHz low-noise amplifier (LNA). It achieves decent 10.6 dB gain tuning range (21.4–10.8 dB) and outstanding 2.11–3.08 dB average noise figure (NFavg) due to adoption of the body-to-source floating …
Artificial bandwidth extension (ABE) approach expands signal bandwidth. In narrowband communication, the ABE approach is used to expand the bandwidth at the receiver end of a narrowband signal. An ABE approach is proposed to improve the perception …
