The $(k,a)$-generalised Fourier transform is the unitary operator defined using $a$-deformed Dunkl harmonic oscillator.The main aim of this paper to prove $L^p$-$L^q$ boundedness $(k, a)$-generalised multipliers. To show we first establish Paley inequality and Hausdorff-Young-Paley for transform. We also demonstrate applications obtained results study well-posedness nonlinear partial differenti...

Document clustering involves repetitive scanning of a document set, therefore as the size of the set increases, the time required for the clustering task increases and may even become impossible due to computational constraints. Compressive sampling is a feature sampling technique that allows us to perfectly reconstruct a vector from a small number of samples, provided that the vector is sparse...

We study the structure and learnability of sums of independent integer random variables (SIIRVs). For k ∈ Z+, a k-SIIRV of order n ∈ Z+ is the probability distribution of the sum of n mutually independent random variables each supported on {0, 1, . . . , k − 1}. We denote by Sn,k the set of all k-SIIRVs of order n. How many samples are required to learn an arbitrary distribution in Sn,k? In thi...

Random and natural textures classification is still one of the biggest challenges in the field of image processing and pattern recognition. In this paper, texture feature extraction using Slant Hadamard Transform was studied and compared to other signal processing-based texture classification schemes. A parametric SHT was also introduced and employed for natural textures feature extraction. We ...

Determination of hypnotizability is important, before prescribing any hypnotic treatment. Existing methods for measuring the level of hypnotic susceptibility are subjective, with some problems. In this study, a feature based on EEG weighted regional frequency was introduced, which can characterize the level of the subject's hypnotizability objectively. The ability of this feature for making a s...

In this study, detection of epileptic seizure has been done using EEG. EEG signal has been decomposed using wavelet transform. After that, features of signal like entropy, variance, maximum value and minimum value of the signal have been calculated. These feature are given to kNN classifier for classification. The accuracy between ICTAL and normal EEG signal (open eye) has been calculated as 10...

In this study, a new supervised noise-artifact-robust heart arrhythmia fusion classification solution, is introduced. Proposed method consists of structurally diverse classifiers with a new QRS complex geometrical feature extraction technique. Toward this objective, first, the events of the electrocardiogram (ECG) signal are detected and delineated using a robust wavelet-based algorithm. Then, ...

We analyze the conformal invariance of submanifold observables associated with k-branes in the AdS/CFT correspondence. For odd k, the resulting observables are conformally invariant, and for even k, they transform with a conformal anomaly that is given by a local expression which we analyze in detail for k = 2.

The problem of computing the eigendecomposition of an N N symmetric matrix is cast as an unconstrained minimization of either of two performance measures. The K = N(N 1)=2 independent parameters represent angles of distinct Givens rotations. Gradient descent is applied to the minimization problem, step size bounds for local convergence are given, and similarities to LMS adaptive filtering are n...

Each Discrete Cosine Transform uses N real basis vectors whose components are cosines. In the DCT-4, for example, the jth component of v k is cos(j + 1 2)(k + 1 2) N. These basis vectors are orthogonal and the transform is extremely useful in image processing. If the vector x gives the intensities along a row of pixels, its cosine series P c k v k has the coeecients c k = (x; v k)=N. They are q...