sapa: Spectral Analysis for Physical Applications. Software for the book Spectral Analysis for Physical Applications, Donald B. Percival and Andrew T. Walden, Cambridge University Press, 1993... The book contains end-of-chapter exercises for the (graduate) student as well as a rather detailed subject index. The software used to produce the numerical examples has been made available by the authors on Internet. The book is well-written and it may find a niche in the literature as an intermediate text between more rigorous mathematically-oriented texts and practically-oriented engineering books.

References in zbMATH (referenced in 85 articles )

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  1. Lauwers, Oliver; Vermeersch, Christof; De Moor, Bart: Cepstral identification of autoregressive systems (2022)
  2. Maddanu, Federico: A harmonically weighted filter for cyclical long memory processes (2022)
  3. Romero, José Luis; Speckbacher, Michael: Spectral-norm risk rates for multi-taper estimation of Gaussian processes (2022)
  4. Hančová, Martina; Gajdoš, Andrej; Hanč, Jozef; Vozáriková, Gabriela: Estimating variances in time series kriging using convex optimization and empirical BLUPs (2021)
  5. Narukawa, Masaki: Efficient tapered local Whittle estimation of multivariate fractional processes (2021)
  6. Sourisseau, Matt; Wang, Yu Guang; Womersley, Robert S.; Wu, Hau-Tieng; Yu, Wei-Hsuan: Improve concentration of frequency and time (ConceFT) by novel complex spherical designs (2021)
  7. Andén, Joakim; Romero, José Luis: Multitaper estimation on arbitrary domains (2020)
  8. Bruce, Scott A.; Tang, Cheng Yong; Hall, Martica H.; Krafty, Robert T.: Empirical frequency band analysis of nonstationary time series (2020)
  9. Cormier, Vernon F.; Tian, Yiteng; Zheng, Yingcai: Heterogeneity spectrum of Earth’s upper mantle obtained from the coherence of teleseismic P waves (2020)
  10. Craigmile, Peter F.; Mondal, Debashis: Estimation of long-range dependence in gappy Gaussian time series (2020)
  11. Monahan, Adam H.: Bispectral unfolding of the skewness of correlated additive and multiplicative noise processes (2020)
  12. Sanna Passino, Francesco; Heard, Nicholas A.: Classification of periodic arrivals in event time data for filtering computer network traffic (2020)
  13. Walden, A. T.; Zhuang, L.: Constructing brain connectivity group graphs from EEG time series (2019)
  14. Zhang, Jiwei; Shao, Yuxiu; Rangan, Aaditya V.; Tao, Louis: A coarse-graining framework for spiking neuronal networks: from strongly-coupled conductance-based integrate-and-fire neurons to augmented systems of ODEs (2019)
  15. Geoga, Christopher J.; Haley, Charlotte L.; Siegel, Andrew R.; Anitescu, Mihai: Frequency-wavenumber spectral analysis of spatio-temporal flows (2018)
  16. Kuske, R.; Lee, C. Y.; Rottschäfer, V.: Patterns and coherence resonance in the stochastic Swift-Hohenberg equation with Pyragas control: the Turing bifurcation case (2018)
  17. Wakaiki, Masashi; Ogura, Masaki; Hespanha, João P.: LQ-optimal sampled-data control under stochastic delays: gridding approach for stabilizability and detectability (2018)
  18. Lepage, Kyle Q.; Vijayan, Sujith: The relationship between coherence and the phase-locking value (2017)
  19. Daubechies, Ingrid; Wang, Yi; Wu, Hau-tieng: ConceFT: concentration of frequency and time via a multitapered synchrosqueezed transform (2016)
  20. Khalid, Zubair; Kennedy, Rodney A.; McEwen, Jason D.: Slepian spatial-spectral concentration on the ball (2016)

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