This book presents practical techniques for estimating frequencies of signals. Includes Matlab code. For researchers.Many signals can be modelled as sums of sinusoids and noise. However, the frequencies of the sinusoids are often unknown and must be estimated to identify the source. This book presents and analyses several practical techniques used for such estimation and for tracking slow frequency changes over time. Rigorous results and physical insight are both given, focusing on noisy signals with large sample sizes. Many applications are described and Matlab code is also included. The book will thus serve as an excellent introduction and reference for researchers analysing such signals.Many signals can be modelled as sums of sinusoids and noise. However, the frequencies of the sinusoids are often unknown and must be estimated to identify the source. This book presents and analyses several practical techniques used for such estimation and for tracking slow frequency changes over time. Rigorous results and physical insight are both given, focusing on noisy signals with large sample sizes. Many applications are described and Matlab code is also included. The book will thus serve as an excellent introduction and reference for researchers analysing such signals.Many electronic and acoustic signals can be modeled as sums of sinusoids and noise. However, the amplitudes, phases and frequencies of the sinusoids are often unknown and must be estimated in order to characterize the periodicity or near-periodicity of a signal and consequently to identify its source. Quinn and Hannan present and analyze several practical techniques used for such estimation. The problem of tracking slow frequency changes of a very noisy sinusoid over time is also considered. Rigorous analyses are presented via asymptotic or large sample theory, together with physical insight. The book focuses on achieving extremely accurate estimates when the signal to noise ratio is low but the sample size isls8