Results 61 to 70 of about 17,761 (290)
Discrete fractional Hilbert transform [PDF]
The Hilbert transform plays an important role in signal processing. A generalization of the Hilbert transform, the fractional Hilbert transform, was recently proposed, and it presents a physical interpretation in the definition. In this paper, we develop the discrete fractional Hilbert transform, and apply the proposed transform to edge detection ...
Pei, Soo-Chang, Yeh, Min-Hung
openaire +4 more sources
ABSTRACT This study examined how Bitcoin, energy prices, and geopolitical risk interact by examining the first four moments (mean, variance, skewness, and kurtosis) of their return distributions by using wavelet analysis. The findings reveal that the co‐movement patterns of energy index, geopolitical risk index, and Bitcoin prices are time and ...
Pooja Kumari+4 more
wiley +1 more source
Abstract We consider a planar Coulomb gas ensemble of size N$N$ with the inverse temperature β=2$\beta =2$ and external potential Q(z)=|z|2−2clog|z−a|$Q(z)=|z|^2-2c \log |z-a|$, where c>0$c>0$ and a∈C$a \in \mathbb {C}$. Equivalently, this model can be realised as N$N$ eigenvalues of the complex Ginibre matrix of size (c+1)N×(c+1)N$(c+1) N \times (c+1)
Sung‐Soo Byun+2 more
wiley +1 more source
Antibiotic‐Induced Microbial Dysbiosis Worsened Outcomes in the Activity‐Based Anorexia Model
ABSTRACT Objective Anorexia nervosa (AN) is a complex psychiatric disorder characterized by persistent dieting and reduced food intake, leading to significantly low body weight. Dysbiosis in the gut microbiome of patients with AN has been suggested to contribute to the pathogenesis.
Karlijn L. Kooij+15 more
wiley +1 more source
Some properties of a modified Hilbert transform
Recently, Steinbach et al. introduced a novel operator $\mathcal{H}_T: L^2(0,T) \rightarrow L^2(0,T)$, known as the modified Hilbert transform. This operator has shown its significance in space-time formulations related to the heat and wave equations. In
Ferrari, Matteo
doaj +1 more source
Bolt Anchorage Quality Levels Classification Method Based on HO‐VMD‐CNN‐BiLSTM
First, the original ultrasound‐guided wave signal data is decomposed into multiple sub‐signals with varying frequencies using VMD to capture the multi‐scale features within the data. Second, the decomposed and noise‐reduced signal, processed by the HO‐VMD algorithm, is input into the CNN for further feature extraction through convolution and pooling ...
Fan Kesong+7 more
wiley +1 more source
A support vector machine (SVM) algorithm was applied to quantitatively predict the connectivity of the sand bodies. Verification using dynamic and static data demonstrated that the prediction accuracy of the algorithm reached 88%. The quantitative sand body connectivity results were used to establish a single sand body model.
Hui He+6 more
wiley +1 more source
Stock Return Prediction Based on a Functional Capital Asset Pricing Model
ABSTRACT The capital asset pricing model (CAPM) is readily used to capture a linear relationship between the daily returns of an asset and a market index. We extend this model to an intraday high‐frequency setting by proposing a functional CAPM estimation approach.
Ufuk Beyaztas+3 more
wiley +1 more source
Classification and Identification of Underwater Target based on Sound Propagation
This paper investigates an underwater noise target classification algorithm in order to identify vessels in shallow water. To this aim the Hilbert Huang transform has been used to extract features in order to be used in a classifier.
Hassan Sayyaadi+2 more
doaj