In this paper we focus on multi-resolution spectral analysis algorithms for music signals based on the FFT. Two previously devised efficient algorithms (efficient constantQ transform [1] and multiresolution FFT [2]) are reviewed and compared with a new proposal based on the IIR filtering of the FFT. Apart from its simplicity, the proposed method shows to be a good compromise between design flex...

It is well-known the fact that the frequency-domain approach obtained by Fourier transforms (FT) can provide amplitude-frequency spectrum while losing time-related information. In non-stationary regime, some of power electronics equipment connected to grid requires time related information, which cannot be provided by FT. Using discrete wavelet transform (DWT), we can preserve the information c...

We introduce the method of dynamic mode decomposition (DMD) for robustly separating complex systems into a hierarchy of multi-resolution time-scaled components. The method includes a methodology for background (low-rank) and foreground (sparse) separation of dynamical data. The method involves a technique used for characterizing nonlinear dynamical systems in an equation-free manner by decompos...

A commonly held view of auditory scene analysis is that complex auditory environments are segregated into separate perceptual streams using primitive cues that can be attended to separately. We argue that this view is inconsistent with the majority of perceptual data reported in the literature and propose an alternative model that is based on a primary, low resolution signal representation used...

In a previous paper we have proven that any multi-resolution analysis of L2(R) produces, for even values of the inverse filling factor and for a square lattice, a single-electron wave function of the lowest Landau level (LLL) which, together with its (magnetic) translated, gives rise to an orthonormal set in the LLL. We have also discussed the inverse construction. In this paper we simplify the...

Image fusion is a process of combining two or more images into an image. It can extract features from source images, and provide more information than one image can. Multi-resolution analysis plays an important role in image processing, it provides a technique to decompose an image and extract information from coarse to fine scales. In some practical forensic examinations (such as the cartridge...

Problems associated with the detection of diseases in their early stage are well known when using chest radiograph images. A graphical method involving wavelet coefficients as the feature vector (WFV) has been proposed for the detection and discrimination of Mycobacterium Tuberculosis (MTB) and lung cancer (LC). In a pilot study confirmed cases showing no complications (for example a section of...

Large data sets arise in a wide variety of applications and are often modeled as samples from a probability distribution in high-dimensional space. It is sometimes assumed that the support of such probability distribution is well approximated by a set of low intrinsic dimension, perhaps even a lowdimensional smooth manifold. Samples are often corrupted by high-dimensional noise. We are interest...

Corresponding to the characteristics of multi-discipline and multi-level management, land administration always requires and acquires spatial data at very different spatial and thematic resolution. This particularity leads to many problems in spatial data acquisition and data management such as: inconsistency and difficulty in exchanging data between data sources and application disciplines. Th...

Community detection is of considerable importance for analyzing the structure and function of complex networks. Many real-world networks may possess community structures at multiple scales, and recently, various multi-resolution methods were proposed to identify the community structures at different scales. In this paper, we present a type of multi-resolution methods by using the generalized se...