Analysis of discrete, time-sampled data using Fourier series method.

摘要: Publisher Summary This chapter outlines a method of Fourier analysis suitable for more general class data. The presents by which the limitations standard are overcome. series technique is valuable tool in data time domain. Typically, experimenter presented with measurements parameter y ( X i ) (hormone concentration, instance) as function independent variable x (usually time). values coefficients that have highest probability, or maximum likelihood, being correct can be obtained. equivalent to least-squares if it assumed assume (1) random experimental uncertainties (noise) described Gaussian distribution, (2) there no systematic data, (3) all dependent variable, (xi), (4) observations (X observations, (5) N large enough provide good sampling uncertainties, and (6) indeed description