Mutual information of IID complex Gaussian signals on block Rayleigh-faded channels

We present a method to compute, quickly and efficiently, the mutual information achieved by an IID (independent identically distributed) complex Gaussian signal on a block Rayleigh-faded channel without side information at the receiver. The method accommodates both scalar and MIMO (multiple-input multiple-output) settings. Operationally, this mutual information represents the highest spectral efficiency that can be attained using Gaussiancodebooks. Examples are provided that illustrate the loss in spectral efficiency caused by fast fading and how that loss is amplified when multiple transmit antennas are used. These examples are further enriched by comparisons with the channel capacity under perfect channel-state information at the receiver, and with the spectral efficiency attained by pilot-based transmission.

Mutual Information of IID complex Gaussian signals on block Rayleigh-faded channels

We present a method to compute, quickly and efficiently, the mutual information achieved by an IID (independent identically distributed) complex Gaussian signal on a block Rayleigh-faded channel without side information at the receiver. The method accommodates both scalar and MIMO (multiple-input multiple-output) settings. Operationally, this mutual information represents the highest spectral efficiency that can be attained using Gaussiancodebooks. Examples are provided that illustrate the loss in spectral efficiency caused by fast fading and how that loss is amplified when multiple transmit antennas are used. These examples are further enriched by comparisons with the channel capacity under perfect channel-state information at the receiver, and with the spectral efficiency attained by pilot-based transmission.

Blind channel deconvolution of real world signals using source separation techniques

In this paper we present a method for blind deconvolution of linear channels based on source separation techniques, for real word signals. This technique applied to blind deconvolution problems is based in exploiting not the spatial independence between signals but the temporal independence between samples of the signal. Our objective is to minimize the mutual information between samples of the output in order to retrieve the original signal. In order to make use of use this idea the input signal must be a non-Gaussian i.i.d. signal. Because most real world signals do not have this i.i.d. nature, we will need to preprocess the original signal before the transmission into the channel. Likewise we should assure that the transmitted signal has non-Gaussian statistics in order to achieve the correct function of the algorithm. The strategy used for this preprocessing will be presented in this paper. If the receiver has the inverse of the preprocess, the original signal can be reconstructed without the convolutive distortion.

A comparative analysis of preprocessing techniques of cardiac event series for the study of heart rhythm variability using simulated signals

In the present study, using noise-free simulated signals, we performed a comparative examination of several preprocessing techniques that are used to transform the cardiac event series in a regularly sampled time series, appropriate for spectral analysis of heart rhythm variability (HRV). First, a group of noise-free simulated point event series, which represents a time series of heartbeats, was generated by an integral pulse frequency modulation model. In order to evaluate the performance of the preprocessing methods, the differences between the spectra of the preprocessed simulated signals and the true spectrum (spectrum of the model input modulating signals) were surveyed by visual analysis and by contrasting merit indices. It is desired that estimated spectra match the true spectrum as close as possible, showing a minimum of harmonic components and other artifacts. The merit indices proposed to quantify these mismatches were the leakage rate, defined as a measure of leakage components (located outside some narrow windows centered at frequencies of model input modulating signals) with respect to the whole spectral components, and the numbers of leakage components with amplitudes greater than 1%, 5% and 10% of the total spectral components. Our data, obtained from a noise-free simulation, indicate that the utilization of heart rate values instead of heart period values in the derivation of signals representative of heart rhythm results in more accurate spectra. Furthermore, our data support the efficiency of the widely used preprocessing technique based on the convolution of inverse interval function values with a rectangular window, and suggest the preprocessing technique based on a cubic polynomial interpolation of inverse interval function values and succeeding spectral analysis as another efficient and fast method for the analysis of HRV signals

Non-negative matrix decomposition approaches to frequency domain analysis of music audio signals

On étudie l’application des algorithmes de décomposition matricielles tel que la Factorisation Matricielle Non-négative (FMN), aux représentations fréquentielles de signaux audio musicaux. Ces algorithmes, dirigés par une fonction d’erreur de reconstruction, apprennent un ensemble de fonctions de base et un ensemble de coef- ficients correspondants qui approximent le signal d’entrée. On compare l’utilisation de trois fonctions d’erreur de reconstruction quand la FMN est appliquée à des gammes monophoniques et harmonisées: moindre carré, divergence Kullback-Leibler, et une mesure de divergence dépendente de la phase, introduite récemment. Des nouvelles méthodes pour interpréter les décompositions résultantes sont présentées et sont comparées aux méthodes utilisées précédemment qui nécessitent des connaissances du domaine acoustique. Finalement, on analyse la capacité de généralisation des fonctions de bases apprises par rapport à trois paramètres musicaux: l’amplitude, la durée et le type d’instrument. Pour ce faire, on introduit deux algorithmes d’étiquetage des fonctions de bases qui performent mieux que l’approche précédente dans la majorité de nos tests, la tâche d’instrument avec audio monophonique étant la seule exception importante.

Quadratic Predictor based Differential Encoding and Decoding of Speech Signals

Modeling nonlinear systems using Volterra series is a century old method but practical realizations were hampered by inadequate hardware to handle the increased computational complexity stemming from its use. But interest is renewed recently, in designing and implementing filters which can model much of the polynomial nonlinearities inherent in practical systems. The key advantage in resorting to Volterra power series for this purpose is that nonlinear filters so designed can be made to work in parallel with the existing LTI systems, yielding improved performance. This paper describes the inclusion of a quadratic predictor (with nonlinearity order 2) with a linear predictor in an analog source coding system. Analog coding schemes generally ignore the source generation mechanisms but focuses on high fidelity reconstruction at the receiver. The widely used method of differential pnlse code modulation (DPCM) for speech transmission uses a linear predictor to estimate the next possible value of the input speech signal. But this linear system do not account for the inherent nonlinearities in speech signals arising out of multiple reflections in the vocal tract. So a quadratic predictor is designed and implemented in parallel with the linear predictor to yield improved mean square error performance. The augmented speech coder is tested on speech signals transmitted over an additive white gaussian noise (AWGN) channel.

The neurochemically diverse intermedius nucleus of the medulla as a source of excitatory and inhibitory synaptic input to the nucleus tractus solitarii

Sensory afferent signals from neck muscles have been postulated to influence central cardiorespiratory control as components of postural reflexes, but neuronal pathways for this action have not been identified. The intermedius nucleus of the medulla (InM) is a target of neck muscle spindle afferents and is ideally located to influence such reflexes but is poorly investigated. To aid identification of the nucleus, we initially produced three-dimensional reconstructions of the InM in both mouse and rat. Neurochemical analysis including transgenic reporter mice expressing green fluorescent protein in GABA-synthesizing neurons, immunohistochemistry, and in situ hybridization revealed that the InM is neurochemically diverse, containing GABAegric and glutamatergic neurons with some degree of colocalization with parvalbumin, neuronal nitric oxide synthase, and calretinin. Projections from the InM to the nucleus tractus solitarius (NTS) were studied electrophysiologically in rat brainstem slices. Electrical stimulation of the NTS resulted in antidromically activated action potentials within InM neurons. In addition, electrical stimulation of the InM resulted in EPSPs that were mediated by excitatory amino acids and IPSPs mediated solely by GABA(A) receptors or by GABA(A) and glycine receptors. Chemical stimulation of the InM resulted in (1) a depolarization of NTS neurons that were blocked by NBQX (2,3-dioxo-6-nitro-1,2,3,4-tetrahydrobenzo[f]quinoxaline-7-sulfonoamide) or kynurenic acid and (2) a hyperpolarization of NTS neurons that were blocked by bicuculline. Thus, the InM contains neurochemically diverse neurons and sends both excitatory and inhibitory projections to the NTS. These data provide a novel pathway that may underlie possible reflex changes in autonomic variables after neck muscle spindle afferent activation.

Are greenhouse gas signals of Northern Hemisphere winter extra-tropical cyclone activity dependent on the identification and tracking algorithm?

For Northern Hemisphere extra-tropical cyclone activity, the dependency of a potential anthropogenic climate change signal on the identification method applied is analysed. This study investigates the impact of the used algorithm on the changing signal, not the robustness of the climate change signal itself. Using one single transient AOGCM simulation as standard input for eleven state-of-the-art identification methods, the patterns of model simulated present day climatologies are found to be close to those computed from re-analysis, independent of the method applied. Although differences in the total number of cyclones identified exist, the climate change signals (IPCC SRES A1B) in the model run considered are largely similar between methods for all cyclones. Taking into account all tracks, decreasing numbers are found in the Mediterranean, the Arctic in the Barents and Greenland Seas, the mid-latitude Pacific and North America. Changing patterns are even more similar, if only the most severe systems are considered: the methods reveal a coherent statistically significant increase in frequency over the eastern North Atlantic and North Pacific. We found that the differences between the methods considered are largely due to the different role of weaker systems in the specific methods.

The chaotic frequency hopping signals for MIMO radar

In multiple-input multiple-output (MIMO) radar systems, the transmitters emit orthogonal waveforms to increase the spatial resolution. New frequency hopping (FH) codes based on chaotic sequences are proposed. The chaotic sequences have the characteristics of good encryption, anti-jamming properties and anti-intercept capabilities. The main idea of chaotic FH is based on queuing theory. According to the sensitivity to initial condition, these sequences can achieve good Hamming auto-correlation while also preserving good average correlation. Simulation results show that the proposed FH signals can achieve lower autocorrelation side lobe level and peak cross-correlation level with the increasing of iterations. Compared to the LFM signals, this sequence has higher range-doppler resolution.

A CMOS/SOI single-input PWM discriminator for low-voltage body-implanted applications

A CMOS/SOI circuit to decode Pulse-Width Modulation (PWM) signals is presented as part of a body-implanted neurostimulator for visual prosthesis. Since encoded data is the sole input to the circuit, the decoding technique is based on a novel double-integration concept and does not require low-pass filtering. Non-overlapping control phases are internally derived from the incoming pulses and a fast-settling comparator ensures good discrimination accuracy in the megahertz range. The circuit was integrated on a 2 mum single-metal thin-film CMOS/SOI fabrication process and has an effective area of 2 mm(2). Measured resolution of encoding parameter a is better than 10% at 6 MHz and V-DD = 3.3 V. Idle-mode consumption is 340 LW. Pulses of frequencies up to 15 MHz and alpha = 10% can be discriminated for 2.3 V less than or equal to V-DD less than or equal to 3.3 V. Such an excellent immunity to V-DD deviations meets a design specification with respect to inherent coupling losses on transmitting data and power by means of a transcutaneous link.

Comparison of EEG signals from epilepsy patients with Bump modeling

Background: l’epilessia è una malattia cerebrale che colpisce oggigiorno circa l’1% della popolazione mondiale e causa, a chi ne soffre, convulsioni ricorrenti e improvvise che danneggiano la vita quotidiana del paziente. Le convulsioni sono degli eventi che bloccano istantaneamente la normale attività cerebrale; inoltre differiscono tra i pazienti e, perciò, non esiste un trattamento comune generalizzato. Solitamente, medici neurologi somministrano farmaci, e, in rari casi, l’epilessia è trattata con operazioni neurochirurgiche. Tuttavia, le operazioni hanno effetti positivi nel ridurre le crisi, ma raramente riescono a eliminarle del tutto. Negli ultimi anni, nel campo della ricerca scientifica è stato provato che il segnale EEG contiene informazioni utili per diagnosticare l'arrivo di un attacco epilettico. Inoltre, diversi algoritmi automatici sono stati sviluppati per rilevare automaticamente le crisi epilettiche. Scopo: lo scopo finale di questa ricerca è l'applicabilità e l'affidabilità di un dispositivo automatico portatile in grado di rilevare le convulsioni e utilizzabile come sistema di monitoraggio. L’analisi condotta in questo progetto, è eseguita con tecniche di misure classiche e avanzate, in modo tale da provare tecnicamente l’affidabilità di un tale sistema. La comparazione è stata eseguita sui segnali elettroencefalografici utilizzando due diversi sistemi di acquisizione EEG: il metodo standard utilizzato nelle cliniche e il nuovo dispositivo portatile. Metodi: è necessaria una solida validazione dei segnali EEG registrati con il nuovo dispositivo. I segnali saranno trattati con tecniche classiche e avanzate. Dopo le operazioni di pulizia e allineamento, verrà utilizzato un nuovo metodo di rappresentazione e confronto di segnali : Bump model. In questa tesi il metodo citato verrà ampiamente descritto, testato, validato e adattato alle esigenze del progetto. Questo modello è definito come un approccio economico per la mappatura spazio-frequenziale di wavelet; in particolare, saranno presenti solo gli eventi con un’alta quantità di energia. Risultati: il modello Bump è stato implementato come toolbox su MATLAB dallo sviluppatore F. Vialatte, e migliorato dall’Autore per l’utilizzo di registrazioni EEG da sistemi diversi. Il metodo è validato con segnali artificiali al fine di garantire l’affidabilità, inoltre, è utilizzato su segnali EEG processati e allineati, che contengono eventi epilettici. Questo serve per rilevare la somiglianza dei due sistemi di acquisizione. Conclusioni: i risultati visivi garantiscono la somiglianza tra i due sistemi, questa differenza la si può notare specialmente comparando i grafici di attività background EEG e quelli di artefatti o eventi epilettici. Bump model è uno strumento affidabile per questa applicazione, e potrebbe essere utilizzato anche per lavori futuri (ad esempio utilizzare il metodo di Sincronicità Eventi Stocas- tici SES) o differenti applicazioni, così come le informazioni estratte dai Bump model potrebbero servire come input per misure di sincronicità, dalle quali estrarre utili risultati.

Sea level measurement using single GNSS antenna SNR signals

This thesis presents a possible method to calculate sea level variation using geodetic-quality Global Navigate Satellite System (GNSS) receivers. Three antennas are used: two small antennas and a choke ring one, analyzing only Global Positioning System signals. The main goal of the thesis is to test a modified configuration for antenna set up. In particular, measurements obtained tilting one antenna to face the horizon are compared to measurements obtained from antennas looking upward. The location of the experiment is a coastal environment nearby the Onsala Space Observatory in Sweden. Sea level variations are obtained using periodogram analysis of the SNR signal and compared to synthetic gauge generated from two independent tide gauges. The choke ring antenna provides poor result, with an RMS around 6 cm and a correlation coefficients of 0.89. The smaller antennas provide correlation coefficients around 0.93. The antenna pointing upward present an RMS of 4.3 cm and the one pointing the horizon an RMS of 6.7 cm. Notable variation in the statistical parameters is found when modifying the length of the interval analyzed. In particular, doubts are risen on the reliability of certain scattered data. No relation is found between the accuracy of the method and weather conditions. Possible methods to enhance the available data are investigated, and correlation coefficient above 0.97 can be obtained with small antennas when sacrificing data points. Hence, the results provide evidence of the suitability of SNR signal analysis for sea level variation in coastal environment even in the case of adverse weather conditions. In particular, tilted configurations provides comparable result with upward looking geodetic antennas. A SNR signal simulator is also tested to investigate its performance and usability. Various configuration are analyzed in combination with the periodogram procedure used to calculate the height of reflectors. Consistency between the data calculated and those received is found, and the overall accuracy of the height calculation program is found to be around 5 mm for input height below 5 m. The procedure is thus found to be suitable to analyze the data provided by the GNSS antennas at Onsala.

The impact of input fluctuations on the frequency-current relationships of layer 5 pyramidal neurons in the rat medial prefrontal cortex

The role of irregular cortical firing in neuronal computation is still debated, and it is unclear how signals carried by fluctuating synaptic potentials are decoded by downstream neurons. We examined in vitro frequency versus current (f-I) relationships of layer 5 (L5) pyramidal cells of the rat medial prefrontal cortex (mPFC) using fluctuating stimuli. Studies in the somatosensory cortex show that L5 neurons become insensitive to input fluctuations as input mean increases and that their f-I response becomes linear. In contrast, our results show that mPFC L5 pyramidal neurons retain an increased sensitivity to input fluctuations, whereas their sensitivity to the input mean diminishes to near zero. This implies that the discharge properties of L5 mPFC neurons are well suited to encode input fluctuations rather than input mean in their firing rates, with important consequences for information processing and stability of persistent activity at the network level.

Perceptual Learning via Modification of Cortical Top-Down Signals

The primary visual cortex (V1) is pre-wired to facilitate the extraction of behaviorally important visual features. Collinear edge detectors in V1, for instance, mutually enhance each other to improve the perception of lines against a noisy background. The same pre-wiring that facilitates line extraction, however, is detrimental when subjects have to discriminate the brightness of different line segments. How is it possible to improve in one task by unsupervised practicing, without getting worse in the other task? The classical view of perceptual learning is that practicing modulates the feedforward input stream through synaptic modifications onto or within V1. However, any rewiring of V1 would deteriorate other perceptual abilities different from the trained one. We propose a general neuronal model showing that perceptual learning can modulate top-down input to V1 in a task-specific way while feedforward and lateral pathways remain intact. Consistent with biological data, the model explains how context-dependent brightness discrimination is improved by a top-down recruitment of recurrent inhibition and a top-down induced increase of the neuronal gain within V1. Both the top-down modulation of inhibition and of neuronal gain are suggested to be universal features of cortical microcircuits which enable perceptual learning.

Are Greenhouse Gas Signals of Northern Hemisphere winter extra-tropical cyclone activity dependent on the identification and tracking algorithm?

For Northern Hemisphere extra-tropical cyclone activity, the dependency of a potential anthropogenic climate change signal on the identification method applied is analysed. This study investigates the impact of the used algorithm on the changing signal, not the robustness of the climate change signal itself. Using one single transient AOGCM simulation as standard input for eleven state-of-the-art identification methods, the patterns of model simulated present day climatologies are found to be close to those computed from re-analysis, independent of the method applied. Although differences in the total number of cyclones identified exist, the climate change signals (IPCC SRES A1B) in the model run considered are largely similar between methods for all cyclones. Taking into account all tracks, decreasing numbers are found in the Mediterranean, the Arctic in the Barents and Greenland Seas, the mid-latitude Pacific and North America. Changing patterns are even more similar, if only the most severe systems are considered: the methods reveal a coherent statistically significant increase in frequency over the eastern North Atlantic and North Pacific. We found that the differences between the methods considered are largely due to the different role of weaker systems in the specific methods.