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Search results for: DECONVOLUTION
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Acceleration of the Discrete Green’s Function Formulation of the FDTD Method Based on Recurrence Schemes
PublicationIn this paper, we investigate an acceleration of the discrete Green's function (DGF) formulation of the FDTD method (DGF-FDTD) with the use of recurrence schemes. The DGF-FDTD method allows one to compute FDTD solutions as a convolution of the excitation with the DGF kernel. Hence, it does not require to execute a leapfrog time-stepping scheme in a whole computational domain for this purpose. Until recently, the DGF generation...
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Optical and structural properties of polycrystalline CVD diamond films grown on fused silica optical fibres pre-treated by high-power sonication seeding
PublicationIn this paper, the growth of polycrystalline chemical vapour deposition (CVD) diamond thin films on fused silica optical fibres has been investigated. The research results show that the effective substrate seeding process can lower defect nucleation, and it simultaneously increases surface encapsulation. However, the growth process on glass requires high seeding density. The effects of suspension type and ultrasonic power were...
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A set of data constituting the basis for the publication entitled "Mitochondria dysfunction is one of the causes of diclofenac toxicity in the green alga Chlamydomonas reinhardtii"
Open Research DataNon-steroidal anti-inflammatory drugs (NSAIDs), such as diclofenac (DCF), form a significant group of environmental contaminants. When the toxic effects of DCF on plants are analyzed, authors often focus on photosynthesis, whilemitochondrial respiration is usually overlooked. Therefore, an in vivo investigation of plant mitochondria functioning under...
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Fusion-based Representation Learning Model for Multimode User-generated Social Network Content
PublicationAs mobile networks and APPs are developed, user-generated content (UGC), which includes multi-source heterogeneous data like user reviews, tags, scores, images, and videos, has become an essential basis for improving the quality of personalized services. Due to the multi-source heterogeneous nature of the data, big data fusion offers both promise and drawbacks. With the rise of mobile networks and applications, UGC, which includes...
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Digital structures for high-speed signal processing
PublicationThe work covers several issues of realization of digital structures for pipelined processing of real and complex signals with the use of binary arithmetic and residue arithmetic. Basic rules of performing operations in residue arithmetic are presented along with selected residue number systems for processing of complex signals and computation of convolution. Subsequently, methods of conversion of numbers from weighted systems to...
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Deep Learning Optimization for Edge Devices: Analysis of Training Quantization Parameters
PublicationThis paper focuses on convolution neural network quantization problem. The quantization has a distinct stage of data conversion from floating-point into integer-point numbers. In general, the process of quantization is associated with the reduction of the matrix dimension via limited precision of the numbers. However, the training and inference stages of deep learning neural network are limited by the space of the memory and a...
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FPGA implementation of the multiplication operation in multiple-precision arithmetic
PublicationAlthough standard 32/64-bit arithmetic is sufficient to solve most of the scientific-computing problems, there are still problems that require higher numerical precision. Multiple-precision arithmetic (MPA) libraries are software tools for emulation of computations in a user-defined precision. However, availability of a reconfigurable cards based on field-programmable gate arrays (FPGAs) in computing systems allows one to implement...
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Cascade Object Detection and Remote Sensing Object Detection Method Based on Trainable Activation Function
PublicationObject detection is an important process in surveillance system to locate objects and it is considered as major application in computer vision. The Convolution Neural Network (CNN) based models have been developed by many researchers for object detection to achieve higher performance. However, existing models have some limitations such as overfitting problem and lower efficiency in small object detection. Object detection in remote...