Spectrum Sensing Algorithms for Cognitive Radio Applications

Future wireless communications systems are expected to be extremely dynamic, smart and capable to interact with the surrounding radio environment. To implement such advanced devices, cognitive radio (CR) is a promising paradigm, focusing on strategies for acquiring information and learning. The first task of a cognitive systems is spectrum sensing, that has been mainly studied in the context of opportunistic spectrum access, in which cognitive nodes must implement signal detection techniques to identify unused bands for transmission. In the present work, we study different spectrum sensing algorithms, focusing on their statistical description and evaluation of the detection performance. Moving from traditional sensing approaches we consider the presence of practical impairments, and analyze algorithm design. Far from the ambition of cover the broad spectrum of spectrum sensing, we aim at providing contributions to the main classes of sensing techniques. In particular, in the context of energy detection we studied the practical design of the test, considering the case in which the noise power is estimated at the receiver. This analysis allows to deepen the phenomenon of the SNR wall, providing the conditions for its existence and showing that presence of the SNR wall is determined by the accuracy of the noise power estimation process. In the context of the eigenvalue based detectors, that can be adopted by multiple sensors systems, we studied the practical situation in presence of unbalances in the noise power at the receivers. Then, we shift the focus from single band detectors to wideband sensing, proposing a new approach based on information theoretic criteria. This technique is blind and, requiring no threshold setting, can be adopted even if the statistical distribution of the observed data in not known exactly. In the last part of the thesis we analyze some simple cooperative localization techniques based on weighted centroid strategies.

The oxidation capacity of the atmosphere - OH and HO 2 radical measurements in a boreal forest environment using laser induced fluorescence spectroscopy

Das wichtigste Oxidationsmittel für den Abbau flüchtiger Kohlenwasserstoffverbindungen (VOC, engl.: volatile organic compounds) in der Atmosphäre ist das Hydroxylradikal (OH), welches sich in einem schnellen chemischen Gleichgewicht mit dem Hydroperoxylradical (HO2) befindet. Bisherige Messungen und Modellvergleiche dieser Radikalspezies in Waldgebieten haben signifikante Lücken im Verständnis der zugrundeliegenden Prozesse aufgezeigt.rnIm Rahmen dieser Doktorarbeit wurden Messungen von OH- und HO2-Radikalen mittelsrnlaserinduzierten Fluoreszensmesstechnik (LIF, engl.: laser-induced fluorescence) in einem Nadelwald in Süd-Finnland während der Messkampagne HUMPPA–COPEC–2010 (Hyytiälä United Measurements of Photochemistry and Particles in Air – Comprehensive Organic Precursor Emission and Concentration study) im Sommer 2010 durchgeführt. Unterschiedliche Komponenten des LIF-Instruments wurden verbessert. Eine modifizierte Methode zur Bestimmung des Hintergrundsignals (engl.: InletPreInjector technique) wurde in den Messaufbaurnintegriert und erstmals zur Messung von atmosphärischem OH verwendet. Vergleichsmessungen zweier Instrumente basierend auf unterschiedlichen Methoden zur Messung von OH-Radikalen, chemische Ionisationsmassenspektrometrie (CIMS - engl.: chemical ionization mass spectrometry) und LIF-Technik, zeigten eine gute Übereinstimmung. Die Vergleichsmessungen belegen das Vermögen und die Leistungsfähigkeit des modifizierten LIF-Instruments atmosphärische OH Konzentrationen akkurat zu messen. Nachfolgend wurde das LIF-Instrument auf der obersten Plattform eines 20m hohen Turmes positioniert, um knapp oberhalb der Baumkronen die Radikal-Chemie an der Schnittstelle zwischen Ökosystem und Atmosphäre zu untersuchen. Umfangreiche Messungen - dies beinhaltet Messungen der totalen OH-Reaktivität - wurden durchgeführt und unter Verwendung von Gleichgewichtszustandsberechnungen und einem Boxmodell, in welches die gemessenen Daten als Randbedingungen eingehen, analysiert. Wenn moderate OH-Reaktivitäten(k′(OH)≤ 15 s−1) vorlagen, sind OH-Produktionsraten, die aus gemessenen Konzentrationen von OH-Vorläuferspezies berechnet wurden, konsistent mit Produktionsraten, die unter der Gleichgewichtsannahme von Messungen des totalen OH Verlustes abgeleitet wurden. Die primären photolytischen OH-Quellen tragen mit einem Anteil von bis zu einem Drittel zur Gesamt-OH-Produktion bei. Es wurde gezeigt, dass OH-Rezyklierung unter Bedingungen moderater OH-Reaktivität hauptsächlich durch die Reaktionen von HO2 mit NO oder O3 bestimmt ist. Während Zeiten hoher OH-Reaktivität (k′(OH) > 15 s−1) wurden zusätzliche Rezyklierungspfade, die nicht über die Reaktionen von HO2 mit NO oder O3, sondern direkt OH bilden, aufgezeigt.rnFür Hydroxylradikale stimmen Boxmodell-Simulationen und Messungen gut übereinrn(OHmod/OHobs=1.04±0.16), während HO2-Mischungsverhältnisse in der Simulation signifikant unterschätzt werden (HO2mod/HO2obs=0.3±0.2) und die simulierte OH-Reaktivität nicht mit der gemessenen OH-Reaktivität übereinstimmt. Die gleichzeitige Unterschätzung der HO2-Mischungsverhältnisse und der OH-Reaktivität, während OH-Konzentrationen von der Simulation gut beschrieben werden, legt nahe, dass die fehlende OH-Reaktivität in der Simulation eine noch unberücksichtigte HO2-Quelle darstellt. Zusätzliche, OH-unabhängigernRO2/HO2-Quellen, wie z.B. der thermische Zerfall von herantransportiertem peroxyacetylnitrat (PAN) und die Photolyse von Glyoxal sind indiziert.

Untersuchungen zur Bedeutung von Histidinkinasen in Magnaporthe oryzae und zum Wirkmechanismus des Fungizids Fludioxonil

Das aus wissenschaftlicher und ökonomischer Sicht wichtigste Pflanzenpathogen M. oryzae entwickelte im Laufe der Evolution konservierte aber auch einzigartige Mechanismen zur Signaltransduktion. Das Erforschen dieser Mechanismen und Prozesse ist essenziell für das Verständnis von Differenzierungsprozessen bei der Pathogen-Wirt-Interaktion.rnIm ersten Teil der vorliegenden Arbeit wurde der Signalweg zur Osmoregulation, der „High Osmolarity Glycerol“ (HOG)-Signalweg, erstmals anhand physiologischer Experimente in entsprechenden Mutantenstämmen in M. oryzae untersucht. Dabei konnten klare Unter-schiede zum HOG-Signalweg von S. cerevisiae aufgezeigt werden. rnDas in M. oryzae bisher noch nicht beschriebene Gen MoYPD1, welches das Phosphotransferprotein MoYpd1p kodiert, wurde erfolgreich inaktiviert. Diese Inaktivierung ist in S. cerevisiae und vielen anderen Pilzen letal und resultierte bei M. oryzae in einer apathoge¬nen Albinomutante, deren Konidiogenese gestört ist. Insbesondere die Funktion des Phosphotransferproteins MoYpd1p, sowohl im Phosphorelaysystem des HOG-Signal¬wegs als auch im Wirkmechanismus des Fungizids Fludioxonil, konnte eindeutig mittels Y2H- und Western Blot-Analysen nachgewiesen werden.rnEs wurden entscheidende Fortschritte für das Verständnis des Aufbaus und der Funktion des HOG-Signalwegs sowohl als physiologisches Regulationssystem für Umweltreize als auch als Fungizidtarget im Pflanzenschutz erzielt. Dabei konnte gezeigt werden, dass die Zweikompo-nenten-Hybrid-Histidinkinase (HIK) MoSln1p als Signalsensor für Salzstress und MoHik1p als Signalsensor für Zuckerstress fungiert. Die Beteiligung der Histidinkinasen MoHik5p und MoHik9p als Sensorproteine für Hypoxie im HOG-Signalweg ist durchaus denk¬bar und wurde durch erste Ergebnisse bekräftigt. rnSo konnte der HOG-Signalweg in mehreren Modellen dargestellt werden. Die Modelle der Signalerkennung und –transduktion von osmotischem Stress, von Hypoxie und der Wirkmecha¬nismus von Fludioxonil wurden erstmals in diesem Umfang für M. oryzae ausgearbei¬tet.rnDer zweite Teil dieser Arbeit repräsentiert die erste umfassende Untersuchung aller zehn HIK-codierender Gensequenzen, die im Genom von M. oryzae identifiziert werden konnten. Diese Signalproteine waren bisher noch nicht Gegenstand wissenschaftlicher Studien. Die Untersuchung beginnt mit einer phylogenetischen Einordnung aller untersuchten Proteinsequen¬zen in die verschiedenen Gruppen von Histidinkinasen in Pilzen. Eine ausführli-che phänotypische Charakterisierung aller HIK-codierender Gene folgt und wurde anhand von Mutanten durchgeführt, in denen diese Gene einzeln inaktiviert wurden.rnDie Beteiligung von MoHik5p und MoHik9p als mögliche Sauerstoffsensoren im HOG-Signal-weg konnte dokumentiert werden und die anschließenden Western Blot-Analysen bestätig¬ten erstmals die Aktivierung des HOG-Signalwegs bei hypoxieähnlichen Zuständen.rnDes Weiteren wurden mit MoHik5p und MoHik8p zwei neue Pathogenitätsfaktoren in M. oryzae identifiziert. Die apathogenen Mutantenstämme ΔMohik5 und ΔMohik8 sind in der Konidiogenese gestört und nicht in der Lage Appressorien zu differenzieren. Der Einsatz dieser Proteine als Fungizidtarget im protektiven Pflanzenschutz in der Zukunft ist somit denk-bar.rn

Dopamine-related deficit in reward learning after catecholamine depletion in unmedicated, remitted subjects with bulimia nervosa

Disturbances in reward processing have been implicated in bulimia nervosa (BN). Abnormalities in processing reward-related stimuli might be linked to dysfunctions of the catecholaminergic neurotransmitter system, but findings have been inconclusive. A powerful way to investigate the relationship between catecholaminergic function and behavior is to examine behavioral changes in response to experimental catecholamine depletion (CD). The purpose of this study was to uncover putative catecholaminergic dysfunction in remitted subjects with BN who performed a reinforcement-learning task after CD. CD was achieved by oral alpha-methyl-para-tyrosine (AMPT) in 19 unmedicated female subjects with remitted BN (rBN) and 28 demographically matched healthy female controls (HC). Sham depletion administered identical capsules containing diphenhydramine. The study design consisted of a randomized, double-blind, placebo-controlled crossover, single-site experimental trial. The main outcome measures were reward learning in a probabilistic reward task analyzed using signal-detection theory. Secondary outcome measures included self-report assessments, including the Eating Disorder Examination-Questionnaire. Relative to healthy controls, rBN subjects were characterized by blunted reward learning in the AMPT-but not in placebo-condition. Highlighting the specificity of these findings, groups did not differ in their ability to perceptually distinguish between stimuli. Increased CD-induced anhedonic (but not eating disorder) symptoms were associated with a reduced response bias toward a more frequently rewarded stimulus. In conclusion, under CD, rBN subjects showed reduced reward learning compared with healthy control subjects. These deficits uncover disturbance of the central reward processing systems in rBN related to altered brain catecholamine levels, which might reflect a trait-like deficit increasing vulnerability to BN.

Two new rapid SNP-typing methods for classifying Mycobacterium tuberculosis complex into the main phylogenetic lineages

There is increasing evidence that strain variation in Mycobacterium tuberculosis complex (MTBC) might influence the outcome of tuberculosis infection and disease. To assess genotype-phenotype associations, phylogenetically robust molecular markers and appropriate genotyping tools are required. Most current genotyping methods for MTBC are based on mobile or repetitive DNA elements. Because these elements are prone to convergent evolution, the corresponding genotyping techniques are suboptimal for phylogenetic studies and strain classification. By contrast, single nucleotide polymorphisms (SNP) are ideal markers for classifying MTBC into phylogenetic lineages, as they exhibit very low degrees of homoplasy. In this study, we developed two complementary SNP-based genotyping methods to classify strains into the six main human-associated lineages of MTBC, the "Beijing" sublineage, and the clade comprising Mycobacterium bovis and Mycobacterium caprae. Phylogenetically informative SNPs were obtained from 22 MTBC whole-genome sequences. The first assay, referred to as MOL-PCR, is a ligation-dependent PCR with signal detection by fluorescent microspheres and a Luminex flow cytometer, which simultaneously interrogates eight SNPs. The second assay is based on six individual TaqMan real-time PCR assays for singleplex SNP-typing. We compared MOL-PCR and TaqMan results in two panels of clinical MTBC isolates. Both methods agreed fully when assigning 36 well-characterized strains into the main phylogenetic lineages. The sensitivity in allele-calling was 98.6% and 98.8% for MOL-PCR and TaqMan, respectively. Typing of an additional panel of 78 unknown clinical isolates revealed 99.2% and 100% sensitivity in allele-calling, respectively, and 100% agreement in lineage assignment between both methods. While MOL-PCR and TaqMan are both highly sensitive and specific, MOL-PCR is ideal for classification of isolates with no previous information, whereas TaqMan is faster for confirmation. Furthermore, both methods are rapid, flexible and comparably inexpensive.

Associative processing and paranormal belief

In the present study we introduce a novel task for the quantitative assessment of both originality and speed of individual associations. This 'BAG' (Bridge-the-Associative-Gap) task was used to investigate the relationships between creativity and paranormal belief. Twelve strong 'believers' and 12 strong 'skeptics' in paranormal phenomena were selected from a large student population (n > 350). Subjects were asked to produce single-word associations to word pairs. In 40 trials the two stimulus words were semantically indirectly related and in 40 other trials the words were semantically unrelated. Separately for these two stimulus types, response commonalities and association latencies were calculated. The main finding was that for unrelated stimuli, believers produced associations that were more original (had a lower frequency of occurrence in the group as a whole) than those of the skeptics. For the interpretation of the result we propose a model of association behavior that captures both 'positive' psychological aspects (i.e., verbal creativity) and 'negative' aspects (susceptibility to unfounded inferences), and outline its relevance for psychiatry. This model suggests that believers adopt a looser response criterion than skeptics when confronted with 'semantic noise'. Such a signal detection view of the presence/absence of judgments for loose semantic relations may help to elucidate the commonalities between creative thinking, paranormal belief and delusional ideation.

School-age children show a bias toward fantasy classifications after playing a platform game

We investigated the influence of playing a video game on children’s ability to distinguish between fantasy and reality. School-age children played a platform game for 15 min and then performed a fantasy/reality distinction task in which they were to judge whether images (from the platform game and from other games) were fantasy images or reality images. Unlike those in the control group (who played a memory game), the children in the experimental group showed a response bias toward mistakenly classifying reality images from the video game as fantasy images (as determined by means of an analysis based on signal detection theory). We conclude that playing the video game exerted a short-term influence on children’s ability to distinguish between fantasy and reality.

Diseño de algoritmos de guerra electrónica y radar para su implementación en sistemas de tiempo real

Esta tesis se centra en el estudio y desarrollo de algoritmos de guerra electrónica {electronic warfare, EW) y radar para su implementación en sistemas de tiempo real. La llegada de los sistemas de radio, radar y navegación al terreno militar llevó al desarrollo de tecnologías para combatirlos. Así, el objetivo de los sistemas de guerra electrónica es el control del espectro electomagnético. Una de la funciones de la guerra electrónica es la inteligencia de señales {signals intelligence, SIGINT), cuya labor es detectar, almacenar, analizar, clasificar y localizar la procedencia de todo tipo de señales presentes en el espectro. El subsistema de inteligencia de señales dedicado a las señales radar es la inteligencia electrónica {electronic intelligence, ELINT). Un sistema de tiempo real es aquel cuyo factor de mérito depende tanto del resultado proporcionado como del tiempo en que se da dicho resultado. Los sistemas radar y de guerra electrónica tienen que proporcionar información lo más rápido posible y de forma continua, por lo que pueden encuadrarse dentro de los sistemas de tiempo real. La introducción de restricciones de tiempo real implica un proceso de realimentación entre el diseño del algoritmo y su implementación en plataformas “hardware”. Las restricciones de tiempo real son dos: latencia y área de la implementación. En esta tesis, todos los algoritmos presentados se han implementado en plataformas del tipo field programmable gate array (FPGA), ya que presentan un buen compromiso entre velocidad, coste total, consumo y reconfigurabilidad. La primera parte de la tesis está centrada en el estudio de diferentes subsistemas de un equipo ELINT: detección de señales mediante un detector canalizado, extracción de los parámetros de pulsos radar, clasificación de modulaciones y localization pasiva. La transformada discreta de Fourier {discrete Fourier transform, DFT) es un detector y estimador de frecuencia quasi-óptimo para señales de banda estrecha en presencia de ruido blanco. El desarrollo de algoritmos eficientes para el cálculo de la DFT, conocidos como fast Fourier transform (FFT), han situado a la FFT como el algoritmo más utilizado para la detección de señales de banda estrecha con requisitos de tiempo real. Así, se ha diseñado e implementado un algoritmo de detección y análisis espectral para su implementación en tiempo real. Los parámetros más característicos de un pulso radar son su tiempo de llegada y anchura de pulso. Se ha diseñado e implementado un algoritmo capaz de extraer dichos parámetros. Este algoritmo se puede utilizar con varios propósitos: realizar un reconocimiento genérico del radar que transmite dicha señal, localizar la posición de dicho radar o bien puede utilizarse como la parte de preprocesado de un clasificador automático de modulaciones. La clasificación automática de modulaciones es extremadamente complicada en entornos no cooperativos. Un clasificador automático de modulaciones se divide en dos partes: preprocesado y el algoritmo de clasificación. Los algoritmos de clasificación basados en parámetros representativos calculan diferentes estadísticos de la señal de entrada y la clasifican procesando dichos estadísticos. Los algoritmos de localization pueden dividirse en dos tipos: triangulación y sistemas cuadráticos. En los algoritmos basados en triangulación, la posición se estima mediante la intersección de las rectas proporcionadas por la dirección de llegada de la señal. En cambio, en los sistemas cuadráticos, la posición se estima mediante la intersección de superficies con igual diferencia en el tiempo de llegada (time difference of arrival, TDOA) o diferencia en la frecuencia de llegada (frequency difference of arrival, FDOA). Aunque sólo se ha implementado la estimación del TDOA y FDOA mediante la diferencia de tiempos de llegada y diferencia de frecuencias, se presentan estudios exhaustivos sobre los diferentes algoritmos para la estimación del TDOA, FDOA y localización pasiva mediante TDOA-FDOA. La segunda parte de la tesis está dedicada al diseño e implementación filtros discretos de respuesta finita (finite impulse response, FIR) para dos aplicaciones radar: phased array de banda ancha mediante filtros retardadores (true-time delay, TTD) y la mejora del alcance de un radar sin modificar el “hardware” existente para que la solución sea de bajo coste. La operación de un phased array de banda ancha mediante desfasadores no es factible ya que el retardo temporal no puede aproximarse mediante un desfase. La solución adoptada e implementada consiste en sustituir los desfasadores por filtros digitales con retardo programable. El máximo alcance de un radar depende de la relación señal a ruido promedio en el receptor. La relación señal a ruido depende a su vez de la energía de señal transmitida, potencia multiplicado por la anchura de pulso. Cualquier cambio hardware que se realice conlleva un alto coste. La solución que se propone es utilizar una técnica de compresión de pulsos, consistente en introducir una modulación interna a la señal, desacoplando alcance y resolución. ABSTRACT This thesis is focused on the study and development of electronic warfare (EW) and radar algorithms for real-time implementation. The arrival of radar, radio and navigation systems to the military sphere led to the development of technologies to fight them. Therefore, the objective of EW systems is the control of the electromagnetic spectrum. Signals Intelligence (SIGINT) is one of the EW functions, whose mission is to detect, collect, analyze, classify and locate all kind of electromagnetic emissions. Electronic intelligence (ELINT) is the SIGINT subsystem that is devoted to radar signals. A real-time system is the one whose correctness depends not only on the provided result but also on the time in which this result is obtained. Radar and EW systems must provide information as fast as possible on a continuous basis and they can be defined as real-time systems. The introduction of real-time constraints implies a feedback process between the design of the algorithms and their hardware implementation. Moreover, a real-time constraint consists of two parameters: Latency and area of the implementation. All the algorithms in this thesis have been implemented on field programmable gate array (FPGAs) platforms, presenting a trade-off among performance, cost, power consumption and reconfigurability. The first part of the thesis is related to the study of different key subsystems of an ELINT equipment: Signal detection with channelized receivers, pulse parameter extraction, modulation classification for radar signals and passive location algorithms. The discrete Fourier transform (DFT) is a nearly optimal detector and frequency estimator for narrow-band signals buried in white noise. The introduction of fast algorithms to calculate the DFT, known as FFT, reduces the complexity and the processing time of the DFT computation. These properties have placed the FFT as one the most conventional methods for narrow-band signal detection for real-time applications. An algorithm for real-time spectral analysis for user-defined bandwidth, instantaneous dynamic range and resolution is presented. The most characteristic parameters of a pulsed signal are its time of arrival (TOA) and the pulse width (PW). The estimation of these basic parameters is a fundamental task in an ELINT equipment. A basic pulse parameter extractor (PPE) that is able to estimate all these parameters is designed and implemented. The PPE may be useful to perform a generic radar recognition process, perform an emitter location technique and can be used as the preprocessing part of an automatic modulation classifier (AMC). Modulation classification is a difficult task in a non-cooperative environment. An AMC consists of two parts: Signal preprocessing and the classification algorithm itself. Featurebased algorithms obtain different characteristics or features of the input signals. Once these features are extracted, the classification is carried out by processing these features. A feature based-AMC for pulsed radar signals with real-time requirements is studied, designed and implemented. Emitter passive location techniques can be divided into two classes: Triangulation systems, in which the emitter location is estimated with the intersection of the different lines of bearing created from the estimated directions of arrival, and quadratic position-fixing systems, in which the position is estimated through the intersection of iso-time difference of arrival (TDOA) or iso-frequency difference of arrival (FDOA) quadratic surfaces. Although TDOA and FDOA are only implemented with time of arrival and frequency differences, different algorithms for TDOA, FDOA and position estimation are studied and analyzed. The second part is dedicated to FIR filter design and implementation for two different radar applications: Wideband phased arrays with true-time delay (TTD) filters and the range improvement of an operative radar with no hardware changes to minimize costs. Wideband operation of phased arrays is unfeasible because time delays cannot be approximated by phase shifts. The presented solution is based on the substitution of the phase shifters by FIR discrete delay filters. The maximum range of a radar depends on the averaged signal to noise ratio (SNR) at the receiver. Among other factors, the SNR depends on the transmitted signal energy that is power times pulse width. Any possible hardware change implies high costs. The proposed solution lies in the use of a signal processing technique known as pulse compression, which consists of introducing an internal modulation within the pulse width, decoupling range and resolution.

Olfactory transduction is intrinsically noisy.

The sources of noise that limit olfactory signal detection were investigated in dissociated rat olfactory receptor cells. Near-threshold odorant-evoked currents exhibited large random fluctuation. However, similar fluctuations were observed in the absence of applied odorants when currents were induced by elevating the intracellular cyclic AMP concentration. This suggests that the fluctuations reflect noise intrinsic to the transduction mechanism, rather than the quantal nature of an odorant stimulus. For many odorants, this intrinsic noise may preclude the reliable detection of single odorant molecules.

Blind multiuser receiver for DS-CDMA wireless system

We consider blind signal detection in an asynchronous code-division multiple-access (CDMA) system employing short spreading sequences in the presence of unknown multipath fading. This approach is capable of countering the presence of multiple-access interference (MAI) in CDMA fading channels. The proposed blind multiuser detector is based on an independent component analysis (ICA) to mitigate both MAI and noise. This algorithm has been utilised in blind source separation (BSS) of unknown sources from their mixtures. It can also be used for estimating the basis vectors of BSS. The aim is to include an ICA algorithm within a wireless receiver in order to reduce the level of interference in wideband systems. This blind multiuser detector requires no training sequence compared with the conventional multiuser detection receiver. The proposed ICA blind multiuser detector is made robust with respect to knowledge of signature waveforms and the timing of the user of interest. Several experiments are performed in order to verify the validity of the proposed ICA algorithm.

Performance analysis using equivariant kernel density estimator in nonlinear mixture

This paper investigates the performance analysis of separation of mutually independent sources in nonlinear models. The nonlinear mapping constituted by an unsupervised linear mixture is followed by an unknown and invertible nonlinear distortion, are found in many signal processing cases. Generally, blind separation of sources from their nonlinear mixtures is rather difficult. We propose using a kernel density estimator incorporated with equivariant gradient analysis to separate the sources with nonlinear distortion. The kernel density estimator parameters of which are iteratively updated to minimize the output independence expressed as a mutual information criterion. The equivariant gradient algorithm has the form of nonlinear decorrelation to perform the convergence analysis. Experiments are proposed to illustrate these results.

Investigating the performance analysis of EASI algorithm and EKENS algorithm in nonlinear model

This paper investigates the performance of EASI algorithm and the proposed EKENS algorithm for linear and nonlinear mixtures. The proposed EKENS algorithm is based on the modified equivariant algorithm and kernel density estimation. Theory and characteristic of both the algorithms are discussed for blind source separation model. The separation structure of nonlinear mixtures is based on a nonlinear stage followed by a linear stage. Simulations with artificial and natural data demonstrate the feasibility and good performance of the proposed EKENS algorithm.

Improved message passing for inference in densely connected systems

An improved inference method for densely connected systems is presented. The approach is based on passing condensed messages between variables, representing macroscopic averages of microscopic messages. We extend previous work that showed promising results in cases where the solution space is contiguous to cases where fragmentation occurs. We apply the method to the signal detection problem of Code Division Multiple Access (CDMA) for demonstrating its potential. A highly efficient practical algorithm is also derived on the basis of insight gained from the analysis. © EDP Sciences.

Discriminating depth in corrugated stereo surfaces: facilitation by a pedestal is explained by removal of uncertainty

With luminance gratings, psychophysical thresholds for detecting a small increase in the contrast of a weak ‘pedestal’ grating are 2–3 times lower than for detection of a grating when the pedestal is absent. This is the ‘dipper effect’ – a reliable improvement whose interpretation remains controversial. Analogies between luminance and depth (disparity) processing have attracted interest in the existence of a ‘disparity dipper’. Are thresholds for disparity modulation (corrugated surfaces), facilitated by the presence of a weak disparity-modulated pedestal? We used a 14-bit greyscale to render small disparities accurately, and measured 2AFC discrimination thresholds for disparity modulation (0.3 or 0.6 c/deg) of a random texture at various pedestal levels. In the first experiment, a clear dipper was found. Thresholds were about 2× lower with weak pedestals than without. But here the phase of modulation (0 or 180 deg) was varied from trial to trial. In a noisy signal-detection framework, this creates uncertainty that is reduced by the pedestal, which thus improves performance. When the uncertainty was eliminated by keeping phase constant within sessions, the dipper effect was weak or absent. Monte Carlo simulations showed that the influence of uncertainty could account well for the results of both experiments. A corollary is that the visual depth response to small disparities is probably linear, with no threshold-like nonlinearity.

Discriminating depth in stereo surfaces: dipper effect found, and lost

Measurement of detection and discrimination thresholds yields information about visual signal processing. For luminance contrast, we are 2 - 3 times more sensitive to a small increase in the contrast of a weak 'pedestal' grating, than when the pedestal is absent. This is the 'dipper effect' - a reliable improvement whose interpretation remains controversial. Analogies between luminance and depth (disparity) processing have attracted interest in the existence of a 'disparity dipper' - are thresholds for disparity, or disparity modulation (corrugated surfaces), facilitated by the presence of a weak pedestal? Lunn and Morgan (1997 Journal of the Optical Society of America A 14 360 - 371) found no dipper for disparity-modulated gratings, but technical limitations (8-bit greyscale) might have prevented the necessary measurement of very small disparity thresholds. We used a true 14-bit greyscale to render small disparities accurately, and measured 2AFC discrimination thresholds for disparity modulation (0.6 cycle deg-1) of a random texture at various pedestal levels. Which interval contained greater modulation of depth? In the first experiment, a clear dipper was found. Thresholds were about 2X1 lower with weak pedestals than without. But here the phase of modulation (0° or 180°) was randomised from trial to trial. In a noisy signal-detection framework, this creates uncertainty that is reduced by the pedestal, thus improving performance. When the uncertainty was eliminated by keeping phase constant within sessions, the dipper effect disappeared, confirming Lunn and Morgan's result. The absence of a dipper, coupled with shallow psychometric slopes, suggests that the visual response to small disparities is essentially linear, with no threshold-like nonlinearity.