Chaos-based communication systems in non-ideal channels

Recently, many chaos-based communication systems have been proposed. They can present the many interesting properties of spread spectrum modulations. Besides, they can represent a low-cost increase in security. However, their major drawback is to have a Bit Error Rate (BER) general performance worse than their conventional counterparts. In this paper, we review some innovative techniques that can be used to make chaos-based communication systems attain lower levels of BER in non-ideal environments. In particular, we succinctly describe techniques to counter the effects of finite bandwidth, additive noise and delay in the communication channel. Although much research is necessary for chaos-based communication competing with conventional techniques, the presented results are auspicious. (C) 2011 Elsevier B. V. All rights reserved.

Efficient sampling of band-limited signals from sine wave crossings

This correspondence presents an efficient method for reconstructing a band-limited signal in the discrete domain from its crossings with a sine wave. The method makes it possible to design A/D converters that only deliver the crossing timings, which are then used to interpolate the input signal at arbitrary instants. Potentially, it may allow for reductions in power consumption and complexity in these converters. The reconstruction in the discrete domain is based on a recently-proposed modification of the Lagrange interpolator, which is readily implementable with linear complexity and efficiently, given that it re-uses known schemes for variable fractional-delay (VFD) filters. As a spin-off, the method allows one to perform spectral analysis from sine wave crossings with the complexity of the FFT. Finally, the results in the correspondence are validated in several numerical examples.

Band-limited airy pulses for invariant propagation in single mode fibers

By spectral analysis, and using joint time-frequency representations, we present the theoretical basis to design invariant band-limited Airy pulses with an arbitrary degree of robustness, and an arbitrary range of single mode fiber chromatic dispersion. The numerically simulated examples confirm the theoretically predicted pulse partial invariance in the propagation of the pulse in the fiber.

Radio-Frequency Interference Identification Over Oceans for C- and X-Band AMSR2 Channels

A new method for radio-frequency interference (RFI) contamination identification over open oceans for the two C-subbands and X-band of Advanced Microwave Scanning Radiometer 2 (AMSR2) channel measurements is suggested. The method is based both on the AMSR2 brightness temperature (T-B) modeling and on the analysis of AMSR2 measurements over oceans. The joint analysis of T-B spectral differences allowed to identify the relations between them and the limits of their variability, which are ensured by the changes in the environmental conditions. It was found that the constraints, based on the ratio of spectral differences, are more regionally and seasonally independent than the spectral differences themselves. Although not all possible RFI combinations are considered, the developed simple criteria can be used to detect most RFI-contaminated pixels over the World Ocean for AMSR2 measurements in two C-subbands and the X-band.

Estimation of Time-Limited Channel Spectra From Nonuniform Samples

This paper deals with the estimation of a time-invariant channel spectrum from its own nonuniform samples, assuming there is a bound on the channel’s delay spread. Except for this last assumption, this is the basic estimation problem in systems providing channel spectral samples. However, as shown in the paper, the delay spread bound leads us to view the spectrum as a band-limited signal, rather than the Fourier transform of a tapped delay line (TDL). Using this alternative model, a linear estimator is presented that approximately minimizes the expected root-mean-square (RMS) error for a deterministic channel. Its main advantage over the TDL is that it takes into account the spectrum’s smoothness (time width), thus providing a performance improvement. The proposed estimator is compared numerically with the maximum likelihood (ML) estimator based on a TDL model in pilot-assisted channel estimation (PACE) for OFDM.

Scalable and efficient data processing in networked control systems

Network control systems (NCSs) are spatially distributed systems in which the communication between sensors, actuators and controllers occurs through a shared band-limited digital communication network. However, the use of a shared communication network, in contrast to using several dedicated independent connections, introduces new challenges which are even more acute in large scale and dense networked control systems. In this paper we investigate a recently introduced technique of gathering information from a dense sensor network to be used in networked control applications. Obtaining efficiently an approximate interpolation of the sensed data is exploited as offering a good tradeoff between accuracy in the measurement of the input signals and the delay to the actuation. These are important aspects to take into account for the quality of control. We introduce a variation to the state-of-the-art algorithms which we prove to perform relatively better because it takes into account the changes over time of the input signal within the process of obtaining an approximate interpolation.

Enhancing the vertical resolution of surface georadar data

There are far-reaching conceptual similarities between bi-static surface georadar and post-stack, "zero-offset" seismic reflection data, which is expressed in largely identical processing flows. One important difference is, however, that standard deconvolution algorithms routinely used to enhance the vertical resolution of seismic data are notoriously problematic or even detrimental to the overall signal quality when applied to surface georadar data. We have explored various options for alleviating this problem and have tested them on a geologically well-constrained surface georadar dataset. Standard stochastic and direct deterministic deconvolution approaches proved to be largely unsatisfactory. While least-squares-type deterministic deconvolution showed some promise, the inherent uncertainties involved in estimating the source wavelet introduced some artificial "ringiness". In contrast, we found spectral balancing approaches to be effective, practical and robust means for enhancing the vertical resolution of surface georadar data, particularly, but not exclusively, in the uppermost part of the georadar section, which is notoriously plagued by the interference of the direct air- and groundwaves. For the data considered in this study, it can be argued that band-limited spectral blueing may provide somewhat better results than standard band-limited spectral whitening, particularly in the uppermost part of the section affected by the interference of the air- and groundwaves. Interestingly, this finding is consistent with the fact that the amplitude spectrum resulting from least-squares-type deterministic deconvolution is characterized by a systematic enhancement of higher frequencies at the expense of lower frequencies and hence is blue rather than white. It is also consistent with increasing evidence that spectral "blueness" is a seemingly universal, albeit enigmatic, property of the distribution of reflection coefficients in the Earth. Our results therefore indicate that spectral balancing techniques in general and spectral blueing in particular represent simple, yet effective means of enhancing the vertical resolution of surface georadar data and, in many cases, could turn out to be a preferable alternative to standard deconvolution approaches.

Irregular to regular sampling, denoising and deconvolution

We propose a restoration algorithm for band limited images that considers irregular(perturbed) sampling, denoising, and deconvolution. We explore the application of a family ofregularizers that allow to control the spectral behavior of the solution combined with the irregular toregular sampling algorithms proposed by H.G. Feichtinger, K. Gr¨ochenig, M. Rauth and T. Strohmer.Moreover, the constraints given by the image acquisition model are incorporated as a set of localconstraints. And the analysis of such constraints leads to an early stopping rule meant to improvethe speed of the algorithm. Finally we present experiments focused on the restoration of satellite images, where the micro-vibrations are responsible of the type of distortions we are considering here. We will compare results of the proposed method with previous methods and show an extension tozoom.

Geostatistical inversion of seismic and GPR reflection images: what can we actually resolve?

Estimation of the spatial statistics of subsurface velocity heterogeneity from surface-based geophysical reflection survey data is a problem of significant interest in seismic and ground-penetrating radar (GPR) research. A method to effectively address this problem has been recently presented, but our knowledge regarding the resolution of the estimated parameters is still inadequate. Here we examine this issue using an analytical approach that is based on the realistic assumption that the subsurface velocity structure can be characterized as a band-limited scale-invariant medium. Our work importantly confirms recent numerical findings that the inversion of seismic or GPR reflection data for the geostatistical properties of the probed subsurface region is sensitive to the aspect ratio of the velocity heterogeneity and to the decay of its power spectrum, but not to the individual values of the horizontal and vertical correlation lengths.

Sparse image reconstruction on the sphere: implications of a new sampling theorem.

We study the impact of sampling theorems on the fidelity of sparse image reconstruction on the sphere. We discuss how a reduction in the number of samples required to represent all information content of a band-limited signal acts to improve the fidelity of sparse image reconstruction, through both the dimensionality and sparsity of signals. To demonstrate this result, we consider a simple inpainting problem on the sphere and consider images sparse in the magnitude of their gradient. We develop a framework for total variation inpainting on the sphere, including fast methods to render the inpainting problem computationally feasible at high resolution. Recently a new sampling theorem on the sphere was developed, reducing the required number of samples by a factor of two for equiangular sampling schemes. Through numerical simulations, we verify the enhanced fidelity of sparse image reconstruction due to the more efficient sampling of the sphere provided by the new sampling theorem.

Steady-spectrum contexts and perceptual compensation for reverberation in speech identification

Perceptual compensation for reverberation was measured by embedding test words in contexts that were either spoken phrases or processed versions of this speech. The processing gave steady-spectrum contexts with no changes in the shape of the short-term spectral envelope over time, but with fluctuations in the temporal envelope. Test words were from a continuum between "sir" and "stir." When the amount of reverberation in test words was increased, to a level above the amount in the context, they sounded more like "sir." However, when the amount of reverberation in the context was also increased, to the level present in the test word, there was perceptual compensation in some conditions so that test words sounded more like "stir" again. Experiments here found compensation with speech contexts and with some steady-spectrum contexts, indicating that fluctuations in the context's temporal envelope can be sufficient for compensation. Other results suggest that the effectiveness of speech contexts is partly due to the narrow-band "frequency-channels" of the auditory periphery, where temporal-envelope fluctuations can be more pronounced than they are in the sound's broadband temporal envelope. Further results indicate that for compensation to influence speech, the context needs to be in a broad range of frequency channels. (c) 2007 Acoustical Society of America.

Reduction of truncation errors in planar, cylindrical and partial spherical near-field antenna measurements

A method to reduce truncation errors in near-field antenna measurements is presented. The method is based on the Gerchberg-Papoulis iterative algorithm used to extrapolate band-limited functions and it is able to extend the valid region of the calculated far-field pattern up to the whole forward hemisphere. The extension of the valid region is achieved by the iterative application of a transformation between two different domains. After each transformation, a filtering process that is based on known information at each domain is applied. The first domain is the spectral domain in which the plane wave spectrum (PWS) is reliable only within a known region. The second domain is the field distribution over the antenna under test (AUT) plane in which the desired field is assumed to be concentrated on the antenna aperture. The method can be applied to any scanning geometry, but in this paper, only the planar, cylindrical, and partial spherical near-field measurements are considered. Several simulation and measurement examples are presented to verify the effectiveness of the method.

How the owl resolves auditory coding ambiguity

The barn owl (Tyto alba) uses interaural time difference (ITD) cues to localize sounds in the horizontal plane. Low-order binaural auditory neurons with sharp frequency tuning act as narrow-band coincidence detectors; such neurons respond equally well to sounds with a particular ITD and its phase equivalents and are said to be phase ambiguous. Higher-order neurons with broad frequency tuning are unambiguously selective for single ITDs in response to broad-band sounds and show little or no response to phase equivalents. Selectivity for single ITDs is thought to arise from the convergence of parallel, narrow-band frequency channels that originate in the cochlea. ITD tuning to variable bandwidth stimuli was measured in higher-order neurons of the owl’s inferior colliculus to examine the rules that govern the relationship between frequency channel convergence and the resolution of phase ambiguity. Ambiguity decreased as stimulus bandwidth increased, reaching a minimum at 2–3 kHz. Two independent mechanisms appear to contribute to the elimination of ambiguity: one suppressive and one facilitative. The integration of information carried by parallel, distributed processing channels is a common theme of sensory processing that spans both modality and species boundaries. The principles underlying the resolution of phase ambiguity and frequency channel convergence in the owl may have implications for other sensory systems, such as electrolocation in electric fish and the computation of binocular disparity in the avian and mammalian visual systems.

FFT Interpolation From Nonuniform Samples Lying in a Regular Grid

This paper presents a method to interpolate a periodic band-limited signal from its samples lying at nonuniform positions in a regular grid, which is based on the FFT and has the same complexity order as this last algorithm. This kind of interpolation is usually termed “the missing samples problem” in the literature, and there exists a wide variety of iterative and direct methods for its solution. The one presented in this paper is a direct method that exploits the properties of the so-called erasure polynomial and provides a significant improvement on the most efficient method in the literature, which seems to be the burst error recovery (BER) technique of Marvasti’s The paper includes numerical assessments of the method’s stability and complexity.

A novel binaural pitch elicited by phase-modulated noise:MEG and psychophysical observations

Binaural pitches are auditory percepts that emerge from combined inputs to the ears but that cannot be heard if the stimulus is presented to either ear alone. Here, we describe a binaural pitch that is not easily accommodated within current models of binaural processing. Convergent magnetoencephalography (MEG) and psychophysical measurements were used to characterize the pitch, heard when band-limited noise had a rapidly changing interaural phase difference. Several interesting features emerged: First, the pitch was perceptually lateralized, in agreement with the lateralization of the evoked changes in MEG spectral power, and its salience depended on dichotic binaural presentation. Second, the frequency of the pure tone that matched the binaural pitch lay within a lower spectral sideband of the phase-modulated noise and followed the frequency of that sideband when the modulation frequency or center frequency and bandwidth of the noise changed. Thus, the binaural pitch depended on the processing of binaural information in that lower sideband.