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Nonlinear Psychophysical Dynamics utilizes new results in systems theory as a foundation for representing sensory channels as a form of recursive loop processes. It demonstrates that a range of phenomena, previously treated as diverse or anomalous, are more readily seen as related and as the natural consequence of self-regulation and nonlinearity. Some cases with appropriate data analysis are reviewed. Quantum Approaches to Consciousness (Stanford Encyclopedia ... It is widely accepted that consciousness or more generally mental activity is in some way correlated to the behavior of the material brain. Since quantum theory is ... The use of fractals for the study of the psychology of ... THE USE OF FRACTALS FOR THE STUDY OF THE PSYCHOLOGY OF PERCEPTION: Psychophysics and Personality Factors A Brief Report . Olga V. Mitina. Moscow State University ... FRANCISCO J. VARELA: 1946-2001 HOME:: Observer Web:: Francisco J. Varela 1946 - 2001: This Focus File is an archival collection of materials on Francisco Varela's life and career. Robotics Institute: Courses The Robotics Institute at Carnegie Mellon University was established in 1979 to conduct basic and applied research in robotics technologies relevant to industrial and ... Theses and Dissertations Available from ProQuest Theses ... Theses and Dissertations Available from ProQuest. Full text is available to Purdue University faculty staff and students on campus through this site. SLAB Neuroscience and Neuroengineering Lab Dendritic excitability in vivo. Neuronal dendrites support a range of nonlinear modes of synaptic integration which can enhance the computational capacity of neural ... Christof Koch - Wikipedia Christof Koch (/ k x /; born November 13 1956) is an American neuroscientist best known for his work on the neural bases of consciousness. He is the President ... Publications Page - Cambridge Machine Learning Group [ full BibTeX file] 2017. Jan-Peter Calliess. Lipschitz optimisation for Lipschitz interpolation. In 2017 American Control Conference (ACC 2017) Seattle WA USA ... Machine Learning Group Publications - University of Cambridge Gaussian Processes and Kernel Methods Gaussian processes are non-parametric distributions useful for doing Bayesian inference and learning on unknown functions. The Personality Project: The measurement of personality More about the personality project. Started in 1995 the Personality-Project is meant to share the excitement of scientific personality theory and research with ...
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