This paper explores the benefits of transforming spectral peaks in voice conversion. First, in examining classic GMMbased transformation with cepstral coefficients, we show that the lack of transformed data variance ("over-smoothing") can be related to the choice of spectral parameterization. Consequently, we propose an alternative parameterization using spectral peaks. The peaks are transforme...

Image fusion is a technique of obtaining high spatial resolution multispectral images from low spatial resolution multispectral and high spatial resolution panchromatic images. Various techniques exist to perform such fusion. These techniques, however, do not seem to preserve the spectral information content of original multispectral image in the fused image. Hence, in this study a recent and e...

A perception and PDE (partial di erential equation) based nonlinear transformation is proposed to process spoken words in noisy environment. The transformation was designed to reduce noise through time adaptation and spectral enhancement by evolving a focusing quadratic fourth order nonlinear PDE (the Cahn-Hillard equation). Constant, low SNR signals were adaptively decreased to reduce noise. O...

The general, linear eigenvalue equations (H XM)z = 0, where H and M are real symmetric matrices with M positive semidefimte, must be transformed if the Lanczos algorithm is to be used to compute eigenpairs (X,z). When the matrices are large and sparse (but not diagonal) some factorization must be performed as part of the transformation step. If we are interested in only a few eigenvalues a near...

This paper proposes a new spectral transformation for speaker normalization. We use the Bilinear Transformation (BLT) to introduce a new frequency warping resulting from a mapping of a prototype Band-Pass (BP) filter into a general BP filter. This new transformation called “Band-Pass Transform” (BPT) offers two degrees of freedom enabling complex warpings of the frequency axis and different fro...

Spectral image analysis problems often begin by applying a transformation that generates an alternative representation of the spectral data with the intention of exposing hidden features not discernable in the original space. We introduce and demonstrate a transformation based on a Markov-chain model of a random walk on a graph via application to spectral image clustering. The random walk is qu...

In this paper, we study explicit correspondences between the integrable Novikov and Sawada–Kotera hierarchies, and between the Degasperis–Procesi and Kaup–Kupershmidt hierarchies. We show how a pair of Liouville transformations between the isospectral problems of the Novikov and Sawada–Kotera equations, and the isospectral problems of the Degasperis–Procesi and Kaup–Kupershmidt equations relate...

We present a new far-field super-resolution imaging approach called compressive spatial to spectral transformation microscopy (CSSTM). The transformation encodes the high-resolution spatial information to a spectrum through illuminating sub-diffraction-limited and wavelength-dependent patterns onto an object. The object is reconstructed from scattering spectrum measurements in the far field. Th...

The total variation (TV) functional is explored from a spectral perspective. We formulate a TV transform based on the second time derivative of the total variation flow, scaled by time. In the transformation domain disks yield impulse responses. This transformation can be viewed as a spectral domain, with somewhat similar intuition of classical Fourier analysis. A simple reconstruction formula ...