David J. Rossi, Alan S. Willsky. / Caption title. "Presented at the 1983 International Conference on Acoustics, Speech and Signal Processing." / Bibliography: leaf [3] / National Science Foundation Grant ECS-8012668

The area of perceptual decision-making research seeks to understand how our perception of the world affects our judgment. Laboratory investigations of perceptual decision-making concentrate on observers' ability to discriminate among stimuli and their biases towards reporting one stimulus more frequently than others. Choice theories assume that these performance measures are determined by generalization of reinforcement along both stimulus and response dimensions. Historically the majority of research has addressed situations in which the difference among stimuli and resulting consequences of a perceptual decision are static. Consequently, little is known about the dynamics of stimulus and response generalization. The present research investigated the dynamics of discrimination accuracy and response bias by frequently varying differences among stimuli and the outcomes for correct decisions. In Experiment 1, four rats responded in a two-stimulus, two-response detection procedure employing temporal stimuli (short vs. long houselight presentations). Sample stimulus difference was varied over two levels across experimental conditions. A rapid acquisition procedure was employed in which relative reinforcer frequency varied daily. Shifts in response bias were well described by a behavioral model of detection (Davison & Nevin, 1999). Within sessions, bias adjusted rapidly to current reinforcer ratios when the sample stimulus difference was large, but not when the difference was small. In Experiment 2, three rats responded in a five-stimulus, two-response detection procedure employing temporal stimuli. Relative reinforcer frequency was again varied daily. Control by current session reinforcer ratios increased rapidly within sessions in a nearly monotonic fashion. Furthermore, response bias following each sample stimulus was observed within the first few trials of an experimental session. The speed of changes in response bias, especially following an unreinforced probe stimulus, provide strong support for an effective reinforcement process and suggest that this process may operate at a trial-by-trial level. In Experiment 3, three rats responded in a six-stimulus, two-response classification procedure. A repeated-acquisition procedure was employed in which the relationship between classes of short and long sample stimuli and their respective correct comparison locations reversed every 15 sessions. After several reversals, the probabilities of reinforcement for correct classification were also manipulated. In the majority of conditions across subjects, response bias reached half-asymptotic levels more rapidly than did discrimination accuracy. These findings provide some support for a backward chaining account of the acquisition of signal detection performance. An attention-augmented behavioral detection model accurately described the acquisition data; however parameter estimates expressing the probability of attending to sample and comparison stimuli differed widely among subjects. The results of these experiments support the adaptation of dynamic research methodologies to the study of learning in perceptual decision-making tasks. Furthermore, discrimination performance and response bias adapt rapidly to frequent changes in reinforcement contingencies. Quantitative models formulated to describe static performance in detection procedures can be extended to predict dynamic performance. Some theoretical assumptions of these models were supported and others were violated. Overall, this research supports a renewed emphasis on learning in signal detection procedures and suggests that stable behavioral endpoints are at least as much a function of contingency variables as they are of sensory variables.

Orientador: Elnatan Chagas Ferreira / Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e de Computação / Made available in DSpace on 2018-08-15T01:31:53Z (GMT). No. of bitstreams: 1 Melo_FernandoFerreirade_D.pdf: 5797933 bytes, checksum: a063234832f57c466d1189c44c7fffaa (MD5) Previous issue date: 2009 / Resumo: Esta tese apresenta o estudo e o projeto de um processador eletrônico do sinal de um interferômetro de Sagnac a fibra óptica que procura atender especificações para aplicação em navegação inercial. Estudou-se o comportamento de Girômetros a fibra óptica com modulação de fase senoidal através de modelos e simulações de algumas técnicas de processamento do sinal fotodetectado. Procurou-se responder questões como o sinal mínimo detectável para processadores de sinal específicos, como a técnica Lock-in e da técnica Mean Value. A técnica Mean Value foi modificada visando facilitar a implementação eletrônica e melhorar o desempenho em relação à proposta original. Compromissos entre estabilidade e pontos de operação com melhor resolução, na medida da diferença de fase de Sagnac, foram estabelecidos para o processador projetado. Este processador foi aplicado a um giroscópio óptico projetado por pesquisadores do IEAv/CTA, em São José dos Campos/SP. / Abstract: This thesis presents the study and design of an electronic signal processor for an optical-fiber Sagnac interferometer aimed at inertial navigation applications. The fiberoptic gyroscope behavior under sinusoidal phase modulations was studied through models and simulation of some signal processing techniques. It was attempted to answer questions like lowest detectable signal for some particular processors, such as synchronous (lock-in) detection and mean value. Modifications to the mean value technique aimed at improving its performance and easing its electronics implementation are presented. Tradeoffs between stability and resolution in Sagnac phase difference measurement were determined for the processor designed and for specific points of operation. This processor was used to extract rotation information from a fiber-optic gyroscope designed and assembled by IEAV/CTA investigators based at São José dos Campos/SP. / Doutorado / Eletrônica, Microeletrônica e Optoeletrônica / Doutor em Engenharia Elétrica

Orientador: Gustavo Fraidenraich / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de Computação / Made available in DSpace on 2018-08-25T18:14:20Z (GMT). No. of bitstreams: 1 Soares_TarcisioAndradePires_M.pdf: 2081899 bytes, checksum: a3053bff77b641167994209d4971dc47 (MD5) Previous issue date: 2014 / Resumo: Este trabalho propõe um estimador ótimo de velocidade utilizando a matriz de covariância da função de máxima verossimilhança para radares de abertura sintética (SAR) com geometria circular, denominados ArcSAR, com alvos distribuídos móveis. Radares ArcSAR podem ser utilizados em aplicações meteorológicas na detecção de nuvens, que são modeladas como alvos distribuídos por refletirem diversos ecos. Este tipo de alvo apresenta algumas dificuldades na estimação de parâmetros por ter seu espectro não simétrico, fazendo o receptor ter um somatório de sinais refletidos. Além desse problema há ainda o ruído que descaracteriza o espectro do sinal recebido e outras complicações que os alvos móveis originam, como mudanças na informação de fase do sinal. Devido à forma de operação do ArcSAR, é necessário estimar a velocidade do alvo de forma precisa para saber a localização geográfica. A estimação do método proposto apresenta o menor erro e a maior precisão dentre os métodos já existentes na literatura. A sua eficiência é comprovada por meio de simulações / Abstract: This work proposes an optimal velocity estimator, using maximum likelihood covariance matrix, for synthetic aperture radars (SAR) with circular geometry, called ArcSAR, with mobiles distributed targets. ArcSAR radars can be used in meteorological applications for detecting clouds, which are modeled as distributed targets due several echo reflections. This kind of target presents some parameters estimation difficulties, because its spectrum is non symmetrical, causing a sum of reflected signals over the receptor. Besides this problem, the noise corrupts the received signal spectrum and there are other complications that mobile targets introduce, like changes at the signal phase information. Due ArcSAR operation, it is necessary a good accuracy on target velocity estimation to know its geographic location. The proposed method estimation presents the lowest error and the best accuracy among the existent methods in the literature. Its accuracy is proven by simulations / Mestrado / Telecomunicações e Telemática / Mestre em Engenharia Elétrica

Orientador: José Cândido Silveira Santos Filho / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de Computação / Made available in DSpace on 2018-08-23T00:47:50Z (GMT). No. of bitstreams: 1 Miranda_MarcoAntonioMiguel_M.pdf: 2405422 bytes, checksum: 5c4caff040f0d11939f7dc322d5df4f3 (MD5) Previous issue date: 2013 / Resumo: Este trabalho analisa a viabilidade de uma nova proposta de radar meteorológico utilizando duas antenas fixas e idênticas, destinado a detectar e localizar fenômenos meteorológicos como chuva e nuvem. Uma das antenas transmite o sinal e recebe os ecos provenientes dos alvos de interesse, caracterizando um radar monoestático, enquanto que a segunda antena apenas recebe os ecos, caracterizando um radar biestático. Para o desenvolvimento de um modelo realístico, medidas de campo utilizando este radar são realizadas, para que o sinal recebido seja caracterizado estatisticamente. Com o modelo estabelecido, é então deduzida uma expressão analítica e geral para o coeficiente de correlação entre os sinais recebidos pelas duas antenas, em função de parâmetros físicos relevantes, tais como a distância entre as antenas (linha de base), a banda do sinal transmitido e a diretividade da antena. Essa análise serve como base para o projeto de um detector para o radar, sob o critério de razão de verossimilhança, em que se procura maximizar a probabilidade de detecção a partir de uma dada probabilidade de falso alarme. No projeto, são evidenciadas a variável e a regra de decisão em função de uma série de amostras dos sinais recebidos. Por fim, apresenta-se uma análise do desempenho do detector projetado para diferentes valores de coeficiente de correlação entre os sinais / Abstract: This work analyzes the feasibility of a new proposal for meteorological radars using two identical fixed spaced antennas, aimed at detecting and locating meteorological phenomena such as rain and clouds. One of the antennas transmits the signal and receives its echoes from the scatterers, characterizing monostatic radar, whereas the other antenna only receives these echoes, characterizing bistatic radar. In order to develop a realistic model, field measurements using this setup are carried out, so that the received signal can be statistically characterized. From this model, it is then derived a general analytical expression for the correlation coefficient of the signals received by the two antennas, as a function of relevant physical parameters, namely distance between antennas (baseline distance), signal bandwidth, and antenna directivity. This analysis is used for the design of a detector for the proposed radar, based on the likelihood ratio method, which intends to maximize the detection probability for a given false-alarm probability. In the design process, the decision variable and the decision rule are properly defined in terms of the set of signals samples. Finally, the performance analysis of the detector is presented for different values of the correlation coefficient between the signals / Mestrado / Telecomunicações e Telemática / Mestre em Engenharia Elétrica

Signal Detection Theory (SDT; Green & Swets, 1966) is a well-established technique to analyze accuracy data in a number of experimental paradigms in psychology, most notably memory and perception, by separating a response bias/criterion from the theoretically bias-free discriminability/sensitivity. As SDT has traditionally been applied, the researcher may be confronted with loss in statistical power and erroneous inferences. A generalized linear mixed-effects modeling (GLMM) approach is presented and advantages with regard to power and precision are demonstrated with an example analysis. Using this approach, a correlation of response bias and sensitivity was detected in the dataset, especially prevalent at the item level, though a correlation between these measures is usually not found to be reported in the memory literature. Directions for future extensions of the method as well as a brief discussion of the correlation between response bias and sensitivity are enclosed. / Graduate / 2019-03-22

Abstract The focus of this thesis is on the binary signal detection problem, i.e., if a signal or signals are present or not. Depending on the application, the signal to be detected can be either unknown or known. The detection is based on some function of the received samples which is compared to a threshold. If the threshold is exceeded, it is decided that signal(s) is (are) present. Energy detectors (radiometers) are often used due to their simplicity and good performance. The main goal here is to develop and analyze energy based detectors as well as power-law based detectors. Different possibilities for setting the detection threshold for a quantized total power radiometer are analyzed. The main emphasis is on methods that use reference samples. In particular, the cell-averaging (CA) constant false alarm rate (CFAR) threshold setting method is analyzed. Numerical examples show that the CA strategy offers the desired false alarm probability, whereas a more conventional strategy gives too high values, especially with a small number of reference samples. New performance analysis of a frequency sweeping channelized radiometer is presented. The total power radiometer outputs from different frequencies are combined using logical-OR, sum and maximum operations. An efficient method is presented for accurately calculating the likelihood ratio used in the optimal detection. Also the effects of fading are analyzed. Numerical results show that although sweeping increases probability of intercept (POI), the final probability of detection is not increased if the number of observed hops is large. The performance of a channelized radiometer is studied when different CFAR strategies are used to set the detection threshold. The proposed iterative methods for setting the detection threshold are the forward consecutive mean excision (FCME) method with the CA scaling factors in final detection decision (FCME+CA), the backward consecutive mean excision (BCME) method with the CA scaling factors in detection (BCME+CA) and a method that uses the CA scaling factors for both censoring and detection (CA+CA). Numerical results show that iterative CFAR methods may improve detection performance compared to baseline methods. Finally, a method to set the threshold of a power-law detector that uses a nonorthogonal transform is presented. The mean, variance and skewness of the decision variable in the noise-only case are derived and these are used to find a shifted log-normal approximation for the distribution of the decision variable. The accuracy of this method is verified through simulations.

Objective: The perceptual mechanisms underlying the development and maintenance of excessive physical symptom reporting (i.e. 'somatisation') are poorly understood. Research with non-clinical participants suggests that high and low symptom reporters perform differently when detecting somatosensory signals and have different false alarm rates in which the presence of a signal is incorrectly reported when no signal is present. High symptom reporters often incorrectly report the presence of a signal particularly when a stimulus in a different sensory modality is presented. Previous research has shown that it may be possible to reduce false alarm rates by perceptual training using bi-modal visuo-tactile stimuli pairing. The current was designed to test this hypothesis. Methods: Seventy non-clinical participants scoring either high or low on the Patient Health Questionnaire (PHQ-15; a measure of somatisation) completed the Somatic Signal Detection Task (SSDT), a novel perceptual paradigm that purports to measure individual differences in somatosensory distortion. Prior to the SSDT, approximately two thirds of the sample completed either a 'weak' or 'strong' perceptual training protocol in which a suprathreshold tactile and visual stimuli were paired either infrequently (25%) or frequently (75%), with the intention of training participants to discriminate tactile signal from noise more effectively. The remaining participants received no perceptual training. Factors known to be strongly associated with somatisation were controlled for. Negative affectivity was controlled for using the State-Trait Anxiety Inventory Trait Version (STAI-T; Spielberger, Gorsuch & Lushene, 1970), somatosensory amplification was controlled for using the Somatosensory Amplification Scale (SSAS; Barsky, Goodson, Lane & Cleary, 1988), the Patient Health Questionnaire (PHQ-9; Kroenke, Spitzer, & Williams, 2001) was used to control for depression and the Health Anxiety Inventory-Short Version (SHAI; Salkovskis, Rimes, Warwick & Clark, 2002) was used to control for hypochondriacal factors with the Patient Health Questionnaire-Generalised Anxiety Disorder (PHQ-GAD-7; Spitzer, Kroenke, Williams & Löwe, 2006) being used to control for anxiety. Results: The high PHQ-15 group reported significantly more false alarms and had a significantly higher response criterion than the low PHQ-15 group in the no perceptual training conditions. The perceptual training reduced the false alarm rate for the high PHQ-15 group but did not alter response criterion. Although the findings were in the predicted direction, neither of these findings reached significance. The effect size indicated that this was due to low power. Conclusions: The findings were suggestive of the effect of perceptual training reducing false alarm rates; however, low power meant that it was impossible to draw firm conclusions. Further research with a larger sample is required.

People’s ability to call an experienced item “old” and a novel item “new” is recognition memory. Recognition memory is usually studied by first asking participants to learn a list of words and then make judgments of old (studied) or new (not studied) for test words. It has long been debated whether the underlying process of recognition memory is continuous or discrete. Two types of models are compared specifically that assume either discrete or continuous information states: the 2-high threshold (2HT) model and the unequal variance signal detection (UVSD) model, respectively. Researchers have used the receiver operation characteristic (ROC) function and response time (RT) data to test between the two models. However, both methods have provided evidence for 2HT and UVSD, and the debate has not come to consensus. In this study, we used an alternative approach to look into this issue. After studying the words, participants first made “old/new” judgment for each single test item. Then, if there were falsely identified items, each of them was randomly paired with a correctly identified word of the same response. Participants were asked to choose the studied word from the word pair. Simulation and experimental results were able to discriminate the 2HT and UVSD model. Experimental results showed that the UVSD model fitted the data better than the 2HT model. The forced-choice test paradigm provided an effective way to test between the 2HT and UVSD models.

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