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As the essence of communication speech intelligibility, rather than more general speech quality, can be of paramount importance when communications systems operate in high noise environments. This paper considers applications where the acoustic signal is degraded by noise so as to be effectively lost and applications where it is simply not available. With such applications in mind we report experiments...
We consider the problem of spectrum estimation of an Auto-Regressive (AR) process in a sparse multipath environment. The presence of even a small number of delayed and attenuated replica of the source signal in the received signal may severely degrade the performance of classical AR spectrum estimation methods. Dwelling on the sparsity of the multipath reflections, we propose an approach which looks...
In this paper, we present a new speech enhancement approach, that is based on exploiting the intra-frame dependency of discrete cosine transform (DCT) domain coefficients. It can be noted that the existing enhancement techniques treat the transformdomain coefficients independently. Instead of this traditional approach of independently processing the scalars, we split the DCT domain noisy speech vector...
Despite the considerable advances in the fabrication processes of imaging sensors, their performance remains limited by theoretical constraints that compromise the achievable sensitivity, frame rate, signal to noise ratio, pixel size and spatial resolution. Therefore, signal processing techniques are needed to improve the final image quality. In this paper, we present a framework for producing a high-resolution...
Localization of an isotropic source using energy measurements from distributed sensors is considered. Usually, such localization techniques require that the distances between the sensor nodes and the source of interest have been previously estimated. This, in turn, requires that sufficient information about the energy decay model as well as the transmit power of the source is available. In this work,...
The objective of the presentation is to examine issues in constraining acoustic-to-articulatory maps by means of facial data and other a priori knowledge regarding speech production. Constraints that are considered are the insertion of data on lip opening, spread and protrusion, as well as other facial data together with constraints on the vocal tract length. A priori knowledge that has been taken...
In this paper, the problem of speech signal under psychological stress is addressed. The investigation into the speaker's stress is based on statistical analysis of glottal pulse derivative extracted from the vowel signals. A pitch synchronous selection of segments from the glottal pulse waveform is used. Selected segments are fixed in their maxima and overlaid. The generated distribution matrix is...
In this paper a modified class of Support Vector Machines (SVMs) inspired from the optimization of Fisher's discriminant ratio is presented. Moreover, we present a novel class of nonlinear decision surfaces by solving the proposed optimization problem in arbitrary Hilbert spaces defined by Mercer's kernels. The effectiveness of the proposed approach is demonstrated by comparing it with the standard...
A new constant modulus algorithm and two of its variants are presented for blind equalisation of complex-valued communication channels. The proposed algorithm is obtained by solving a novel deterministic optimisation criterion which comprises the dispersion minimisation of a priori as well as a posteriori quantities leading to an update equation having a particular zero-memory continuous nonlinearity...
Old printed photos are affected by several typical damages, due to age and bad preservation. “Foxing” defects look like red-brownish spots onto the paper of the printed photo. Similar features can be seen in the digitized copies. In this paper we propose a set of low level descriptors to extract features from digitized photos affected by foxing. An image retrieval application, based on information...
This paper introduces a numerical model for the simulation of chaos-modulated dual oscillator-based random number generators. Random number generation method based on dual oscillator architecture is described. Developed model allows the estimation of the output entropy and bias as a function of design parameters, thus provides determination of these parameters for a continuous-time chaotic source...
In this paper, we propose a method to embed the high resolution color information of an image in its corresponding grey-level image. The objective of this work is to allow free access to the grey-level image and give high resolution color image access to secret key owners. This method is made of two steps which are the color image decomposition (in a grey-level image and its associated color information)...
In this paper we present a novel full-rate and full-diversity quasi-orthogonal space-time block coding scheme for use in asynchronous cooperative relay networks. A variant of orthogonal frequency division multiplexing (OFDM) is implemented at the source node to mitigate the effects of random delays at the relay nodes, which operate in a simple amplify-and-forward mode. Utilizing a feedback channel,...
An empirical formulation that relates the filter length, the transition bandwidth, the cutoff frequency, the maximum passband ripple magnitude, the maximum stopband ripple magnitude and the total ripple energy of symmetric/anti-symmetric finite impulse response (FIR) single band peak constrained least squares (PCLS) filters is presented. Design examples are presented to demonstrate the application...
Recently, marginalized particle filter (MPF) has been applied to blind symbol detection problems over selective fading channels. By marginalizing out the state appearing linearity and Gaussianity in the dynamics, the MPF can reduce the computational complexity, which is one of the main drawbacks of the standard particle filters. In this paper, we consider application of the MPF to the problem of blind...
We present a novel technique for joint deblurring and demosaicing of noisy Poissonian Bayer data (e.g., data acquired by a digital CMOS or CCD imaging sensor). The technique incorporates the regularized inverse and the Wiener inverse with adaptive filtering based on the concept of cross-color local polynomial approximation (LPA) and intersection of confidence intervals (ICI). The directional filters...
In this study, an adaptive autoregressive (AR) algorithm is proposed for the blind identification and equalization of finite impulse response (FIR) channels for chaotic communication systems. The AR method is derived by minimizing a nonlinear prediction error function that is calculated by exploiting the short time predictability of a chaotic signal. The adaptive AR algorithm requires a recursion...
Image registration plays a critically important role in remote sensing applications. Due to the large volumes of remote-sensing data available today, automated registration of multitemporal and/or multisensor images is highly desired. In this work, a new automatic approach for elastic image registration of remotely sensed images is proposed. The critical elements for an automated image registration...
We study adaptive-playout scheduling for VoIP using the framework of stochastic impulse control theory. A Wiener process is introduced to model the fluctuation of the buffer length in the absence of control. In this context, the control signal consists of length units that correspond to inserting or dropping a pitch cycle. We define an optimality criterion that has an adjustable trade-off between...
Clean documents are relatively easy to recognize. However, when digitizing collections of documents, the clean ones are rarely the documents that are encountered. The processes of printing and scanning documents introduce image degradations that interfere with the segmentation and recognition processes. Mathematical models of the degradation processes are presented. From these the types of degradations...
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