Parameter Selection and Optimization in Brain Wave Research
The increasingly important role of mathematical methods and computer analysis in brain wave research has created an urgent need to effectively communicate mathematical and computational concepts to neurophysiologists and other medical investigators engaged in behavioral and clinical research. I hope this paper will partly serve that need. The material presented is not intended as a mathematically rigorous treatment of parameter abstraction, but rather as a neurophysiologically motivated introduction to the mathematical notions underlying the selection and measurement of certain parameters. The ultimate objective is the correlation of these parameters with neurophysiological factors as a basis for studying the electrical activity of the brain and behavior.
KeywordsAttenuation Radar Coherence Autocorrelation Convolution
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- Blackman, R.B., and Tukey, J.W. 1958. The Measurement of Power Spectra. New York: Dover.Google Scholar
- Bogert, B., Healy, M., and Tukey, J. 1963. The frequency analysis of time series for echoes. In M. Rosenblatt Ed.), Proceedings of Symposium on Time Series Analysis, p. 209. New York: Wiley.Google Scholar
- Oppenheim, A.V. 1965. Superposition in a class of non-linear systems. Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, Mass. Technical Report 432.Google Scholar
- Oppenheim, A.V. 1965. Optimum homomorphic filters. Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, Mass. Quarterly Progress Reports 77:248.Google Scholar
- Oppenheim, A.V. 1966. Non-linear filtering of convolved signals. Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, Mass. Quarterly Progress Reports 80:168.Google Scholar
- Robinson, E.A. 1959. An Introduction to Infinitely Many Variates. New York: Hafner.Google Scholar
- Saltzberg, B. 1971. Digital filters in neurological research. Proceedings Symposium on Digital Filtering. London: Imperial College of Science and Technology.Google Scholar
- Saltzberg, B. 1973. Analysis of developmental electrophysiology. Tulane University School of Medicine, New Orleans, La. Annual Progress Report NINDS Grant 09332.Google Scholar
- Schafer, R.W. 1967. Echo removal by generalized linear filtering. NEREM Record p. 118.Google Scholar
- Senmoto, S., and Childers, D.G. 1972. Adaptive decomposition of a composite signal of identical unknown wavelets in noise. IEEE Transactions on Systems, Man, and Cybernetics, SMC-2, 1:59.Google Scholar
- Siegel, S. 1956. Nonparametric Statistics. New York: McGraw-Hill.Google Scholar