Results 71 to 80 of about 2,434,155 (179)

Recommendations for quantitative cerebral perfusion MRI using multi‐timepoint arterial spin labeling: Acquisition, quantification, and clinical applications

open access: yesMagnetic Resonance in Medicine, Volume 92, Issue 2, Page 469-495, August 2024.
Abstract Accurate assessment of cerebral perfusion is vital for understanding the hemodynamic processes involved in various neurological disorders and guiding clinical decision‐making. This guidelines article provides a comprehensive overview of quantitative perfusion imaging of the brain using multi‐timepoint arterial spin labeling (ASL), along with ...
Joseph G. Woods   +33 more
wiley   +1 more source

Multiallelic Walsh transforms [PDF]

open access: yes, 2023
A closed formula multiallelic Walsh (or Hadamard) transform is introduced. Basic results are derived, and a statistical interpretation of some of the resulting linear forms is ...
Greene, Devin
core  

TCM, TTCM, BICM and BICM-ID Assisted MMSE Multi-User Detected SDMA-OFDM Using Walsh-Hadamard Spreading

open access: yes, 2004
Space Division Multiple Access (SDMA) aided Orthogonal Frequency Division Multiplexing (OFDM) systems assisted by efficient Multi-User Detection (MUD) techniques have recently attracted intensive research interests. Forward Error Correction (FEC) schemes
Jiang, M., Ng, S. X., Hanzo, L.
core   +1 more source

Improved Quantum Linear Attacks and Application to CAST

open access: yesIACR Transactions on Symmetric Cryptology
This paper studies quantum linear key-recovery attacks on block ciphers. The first such attacks were last-rounds attacks proposed by Kaplan et al. (ToSC 2016), which combine a linear distinguisher with a guess of a partial key.
Kaveh Bashiri   +4 more
doaj   +1 more source

A bit level systolic array for Walsh-Hadamard transforms

open access: yes, 2012
[[abstract]]The Walsh-Hadamard transforms are very important in image data compression, filtering and design of codes. Recently, a systolic array for the Hadamard transform was developed for the speed of computation.
Long-Wen Chang;Ming-Chang Wu
core   +1 more source

Root-Hadamard transforms and complementary sequences [PDF]

open access: yes, 2019
The article of record as published may be found at https://doi.org/10.1007/s12095-020-00440-4In this paper we define a new transform on (generalized) Boolean functions, which generalizes the Walsh-Hadamard, nega-Hadamard, 2k-Hadamard, consta-Hadamard ...
Riera, Constanza   +3 more
core   +2 more sources

Cancelable speaker identification system for the handicapped access to healthcare networks

open access: yesJournal of Electrical Systems and Information Technology
One of the most promising applications of speaker recognition technology is to assist individuals with disabilities. With the rapid advancement of the Internet of Things (IoT), integrating speaker recognition into IoT devices is becoming increasingly ...
Samia A. El-Moneim Kabel   +4 more
doaj   +1 more source

Use of fast Walsh-Hadamard transformation for optimalsymbol-by-symbol binary block-code decoding

open access: yesElectronics Letters, 1998
A procedure for optimal symbol-by-symbol binary block-code decoding is presented: it uses the spectral Walsh-Hadamard transformation. The dimension of the Walsh-Hadamard basis is equal to that of dual codes. The realisation of the described procedure, using the fast Walsh-Hadamard transformation application, is seen to be the most efficient in terms of
L.E. Nazarov, V.M. Smolyaninov
openaire   +1 more source

Algorithms for Fine-grained Architecture Implementation of 2-dimensional Fast Walsh-Hadamard Transforms

open access: yes, 1990
Spatial transforms play a central role in image and signal processing applications. The Walsh-Hadamard Transform, due to its simple integer basis functions, provides superior computational simplicity and minimal memory requirements.
Lai, Shuk Fong
core  

Hadamard Walsh space based hybrid technique for image data augmentation [PDF]

open access: yes
Image data augmentation (IDA) is common when deep learning is used for image classification to address the issue of overfitting. Overfitting occurs when the datasets are small and the deep learning models have a huge capacity. Overfitting models have low
Suryawanshi, Vaishali, Sarode, Tanuja K.
core   +1 more source

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