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Detection of rotating gravity signals
Biological Cybernetics, 1992It is shown in the preceding paper that neurons with two-dimensional spatio-temporal properties to linear acceleration behave like one-dimensional rate sensors: they encode the component of angular velocity (associated with a rotating linear acceleration vector) that is normal to their response plane.
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2012
Signal detection theory (SDT), developed in the 1950s, is a framework of statistical methods used to model how observers classify sensory events [72, 169]. In this chapter we describe commonly used signal detection models and methods for fitting them. A recurring theme in this book is the use of the generalized linear model (GLM) to fit psychophysical ...
Kenneth Knoblauch, Laurence T. Maloney
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Signal detection theory (SDT), developed in the 1950s, is a framework of statistical methods used to model how observers classify sensory events [72, 169]. In this chapter we describe commonly used signal detection models and methods for fitting them. A recurring theme in this book is the use of the generalized linear model (GLM) to fit psychophysical ...
Kenneth Knoblauch, Laurence T. Maloney
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Signal Estimation and Signal Detection
1998The previous chapter has introduced and discussed TF projection filters that pass signals located in a given TF region and suppress signals located outside this TF region. So far, these filters have been studied mainly in a deterministic setting. In this chapter, we shall consider a stochastic setting and discuss applications of TF projection filters ...
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2002
Abstract Any psychophysical task has cognitive components, this term covering a variety of such factors as response bias, guessing strategy, motivation, etc. So far in our approach to psychophysical theory, we have implicitly assumed that such factors could be bypassed or controlled by careful experimental design.
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Abstract Any psychophysical task has cognitive components, this term covering a variety of such factors as response bias, guessing strategy, motivation, etc. So far in our approach to psychophysical theory, we have implicitly assumed that such factors could be bypassed or controlled by careful experimental design.
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2014
Abstract In distributed signal detection, multiple sensors work together to distinguish between the absence of presence of a signal of interest. Sensors transmit their measurements to a central node called fusion center which is responsible for the inference. In this chapter, we first review the theory of obtaining optimal decision rules at the local
Pramod K. Varshney, Engin Masazade
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Abstract In distributed signal detection, multiple sensors work together to distinguish between the absence of presence of a signal of interest. Sensors transmit their measurements to a central node called fusion center which is responsible for the inference. In this chapter, we first review the theory of obtaining optimal decision rules at the local
Pramod K. Varshney, Engin Masazade
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Optimal Signal Detection and Tracking of Detected Signals
Journal of Automation and Information Sciences, 2000Nataliya G. Vovkodav +1 more
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The dynamic control of signal transduction networks in cancer cells
Nature Reviews Cancer, 2015Walter Kolch +2 more
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