Detection of Focal and Non-Focal Electroencephalogram Signals Using Fast Walsh-Hadamard Transform and Artificial Neural Network. [PDF]
Sensors (Basel), 2020 The discrimination of non-focal class (NFC) and focal class (FC), is vital in localizing the epileptogenic zone (EZ) during neurosurgery. In the conventional diagnosis method, the neurologist has to visually examine the long hour electroencephalogram ...
J P +6 more
europepmc +4 more sources
Pauli decomposition via the fast Walsh-Hadamard transform [PDF]
New Journal of PhysicsThe decomposition of a square matrix into a sum of Pauli strings is a classical pre-processing step required to realize many quantum algorithms. Such a decomposition requires significant computational resources for large matrices. We present an exact and
Timothy N Georges +3 more
doaj +3 more sources
High-Capacity Image Steganography Based on Discrete Hadamard Transform
IEEE Access, 2022 High capacity and high imperceptibility are the primary targets for ideal image steganography. For the traditional transform-based schemes, the main challenge is to balance the imperceptibility, hiding capacity, and running efficiency.
Ying-Qian Zhang +2 more
doaj +2 more sources
Enhancing Tool Wear Prediction Accuracy Using Walsh-Hadamard Transform, DCGAN and Dragonfly Algorithm-Based Feature Selection. [PDF]
Sensors (Basel), 2023 Tool wear is an important concern in the manufacturing sector that leads to quality loss, lower productivity, and increased downtime. In recent years, there has been a rise in the popularity of implementing TCM systems using various signal processing ...
Shah M +5 more
europepmc +2 more sources
Fast Walsh-Hadamard Transform and Smooth-Thresholding Based Binary Layers in Deep Neural Networks [PDF]
2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2021 In this paper, we propose a novel layer based on fast Walsh-Hadamard transform (WHT) and smooth-thresholding to replace 1 × 1 convolution layers in deep neural networks. In the WHT domain, we denoise the transform domain coefficients using the new smooth-
Hongyi Pan +2 more
openalex +3 more sources
The Sufficient Condition for Ensuring the Reliability of Perception of the Steganographic Message in the Walsh-Hadamard Transform Domain [PDF]
Problems of the Regional Energetics, 2022 In view of the high compatibility of the Walsh-Hadamard transform to the architecture of mod-ern computing facilities, it is sensible to use it in methods of steganography and steganalysis.
Kobozeva A.A., Sokolov A.V.
doaj +1 more source
A novel blockchain-watermarking mechanism utilizing interplanetary file system and fast walsh hadamard transform. [PDF]
iScienceLiu T, Lai SN, Yuan X, Liu Y, Lam CT.
europepmc +3 more sources
A Hybrid Quantum-Classical Approach based on the Hadamard Transform for the Convolutional Layer [PDF]
International Conference on Machine Learning, 2023 In this paper, we propose a novel Hadamard Transform (HT)-based neural network layer for hybrid quantum-classical computing. It implements the regular convolutional layers in the Hadamard transform domain.
Hongyi Pan, Xin Zhu, S. Atici, A. Cetin
semanticscholar +1 more source
Cascaded, self-calibrated, single-pixel mid-infrared Hadamard transform spectrometer
Optics Express, 2021 In this paper, a single-pixel mid-infrared (mid-IR) Hadamard transform spectrometer is developed. The spectrometer's design, fabrication and experimental results are discussed.
Zi Heng Lim +5 more
openalex +2 more sources
Block Walsh–Hadamard Transform-based Binary Layers in Deep Neural Networks [PDF]
ACM Transactions on Embedded Computing Systems, 2022 Convolution has been the core operation of modern deep neural networks. It is well known that convolutions can be implemented in the Fourier Transform domain.
Hongyi Pan, Diaa Badawi, A. Cetin
semanticscholar +1 more source