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Silicon photo-multipliers (SiPM) have been replacing traditional photomultiplier tubes in most light sensing applications. However, when large detection surface coverage is needed, photomultipliers (PMTs) are still the preferred choice. The…
Over the last decade, a number of Computational Imaging (CI) systems have been proposed for tasks such as motion deblurring, defocus deblurring and multispectral imaging. These techniques increase the amount of light reaching the sensor via…
Power converters require passive low-pass filters which are capable of reducing voltage ripples effectively. In contrast to signal filters, the components of power filters must carry large currents or withstand large voltages, respectively.…
In this paper, the design of a computationally efficient variable bandpass digital filter is presented. The center frequency and bandwidth of this filter can be changed online without updating the filter coefficients. The warped filters,…
The photovoltaic microinverter based two-switch DC-DC flyback converters has been investigated. The microinverter is characterized by the high performance and simple design. The effect of CL and LCL low pass filter on Total Harmonics…
Capturing high-dimensional (HD) data is a long-term challenge in signal processing and related fields. Snapshot compressive imaging (SCI) uses a two-dimensional (2D) detector to capture HD ($\ge3$D) data in a {\em snapshot} measurement. Via…
Indoor visible light communication (VLC) is a promising sixth-generation (6G) technology, as its directional and sensitive optical signals are naturally suited for integrated sensing and communication (ISAC). However, current research…
We present the design, fabrication, and measurement of a high-temperature superconductor (HTSC) Stepped Impedance Resonator (SIR) band-pass filter for S-band applications, and its incorporation into a cryogenic receiver cascade. The 11-pole…
Light detection and ranging (LIDAR) is critical to many fields in science and industry. Over the last decade, optical frequency combs were shown to offer unique advantages in optical ranging, in particular when it comes to fast distance…
This paper describes a direct conversion receiver applying compressed sensing with the objective to relax the analog filtering requirements seen in the traditional architecture. The analog filter is cumbersome in an \gls{IC} design and…
We focus on controllable disentangled representation learning (C-Dis-RL), where users can control the partition of the disentangled latent space to factorize dataset attributes (concepts) for downstream tasks. Two general problems remain…
Questing for learned lossy image coding (LIC) with superior compression performance and computation throughput is challenging. The vital factor behind it is how to intelligently explore Adaptive Neighborhood Information Aggregation (ANIA)…
While coarse-grained reconfigurable arrays (CGRAs) have emerged as promising programmable accelerator architectures, pipelining applications running on CGRAs is required to ensure high maximum clock frequencies. Current CGRA compilers…
Hyperspectral image classification (HIC) is an active research topic in remote sensing. Hyperspectral images typically generate large data cubes posing big challenges in data acquisition, storage, transmission and processing. To overcome…
The reconstruction of sparse signals from a limited set of measurements poses a significant challenge as it necessitates a solution to an underdetermined system of linear equations. Compressed sensing (CS) deals with sparse signal…
Over the past few decades there has been a strong effort towards the development of Smoothness-Increasing Accuracy-Conserving (SIAC) filters for Discontinuous Galerkin (DG) methods, designed to increase the smoothness and improve the…
While there exists a rich array of matrix column subset selection problem (CSSP) algorithms for use with interpolative and CUR-type decompositions, their use can often become prohibitive as the size of the input matrix increases. In an…
Weakly-supervised image segmentation (WSIS) is a critical task in computer vision that relies on image-level class labels. Multi-stage training procedures have been widely used in existing WSIS approaches to obtain high-quality pseudo-masks…
We study linear filters for processing signals supported on abstract topological spaces modeled as simplicial complexes, which may be interpreted as generalizations of graphs that account for nodes, edges, triangular faces etc. To process…
A digital-assisted photonic analog wideband radio-frequency multipath self-interference cancellation (SIC) and frequency downconversion method based on a dual-drive Mach-Zehnder modulator and the recursive least square (RLS) algorithm is…