This article deals with the estimation of model-based parameters, such as the noise variance and signal components, from magnitude magnetic resonance (MR) images. Special attention has been paid to the estimation of T1and T2-relaxation parameters. It is shown that most of the conventional estimation methods, when applied to magnitude MR images, yield biased results. Also, it is shown how the kn...

Various axiomatic theories of magnitude estimation are presented. The axioms are divided into the following categories: behavioral, in which the primitive relationships are in principle observable by the experimenter; cognitive, in which the primitive relationships are theoretical in nature and deal with subjective relationships that the subject is supposedly using in making his or her magnitud...

Our representation of the physical world requires judgments of magnitudes, such as loudness, distance, or time. Interestingly, magnitude estimates are often not veridical but subject to characteristic biases. These biases are strikingly similar across different sensory modalities, suggesting common processing mechanisms that are shared by different sensory systems. However, the search for unive...

This paper provides a generic equation for the evaluation of the maximum earthquake magnitude mmax for a given seismogenic zone or entire region. The equation is capable of generating solutions in different forms, depending on the assumptions of the statistical distribution model and/or the available information regarding past seismicity. It includes the cases (i) when earthquake magnitudes are...

One class of models assumes that presentation of a signal results in an internal representation as a random variable. Depending on whether the signal is close to or far from the preceding signal, the variance of the representation is smaller or larger. Responses are determined largely by this random variable; however, when the signal is close to the preceding one, the response is generated by m...