01007nam0 22002651i 450 UON0042163220231205104826.47720130403d1967 |0itac50 bafreFR|||| 1||||André Gide and the greek mytha critical study by Helen Watson-WilliamsOxfordClarendon Press1967xiii, 200 p.23 cm.GIDE ANDRE'UONC043158FIGBOxfordUONL000029844Letteratura francese. Saggi21WATSON-WILLIAMSHelenUONV214923710505Clarendon PressUONV246509650ITSOL20240220RICASIBA - SISTEMA BIBLIOTECARIO DI ATENEOUONSIUON00421632SIBA - SISTEMA BIBLIOTECARIO DI ATENEOSI Francese VI A GID WAT SI SFR4096 5 BuonoAndré Gide and the greek myth1333663UNIOR03991nam 22006135 450 991098308900332120250630101745.03-031-71093-210.1007/978-3-031-71093-3(CKB)36338358700041(MiAaPQ)EBC31743917(Au-PeEL)EBL31743917(DE-He213)978-3-031-71093-3(EXLCZ)993633835870004120241002d2025 u| 0engur|||||||||||txtrdacontentcrdamediacrrdacarrierNoise signals Modelling and Analyses /by Vitalii Babak, Artur Zaporozhets, Yurii Kuts, Mykhailo Fryz, Leonid Scherbak1st ed. 2025.Cham :Springer Nature Switzerland :Imprint: Springer,2025.1 online resource (232 pages)Studies in Systems, Decision and Control,2198-4190 ;5673-031-71092-4 Chapter 1. Problems of Noise Signals Research -- Chapter 2. Linear Models of Stochastic Noise Signals -- Chapter 3. Periodic Models of Noise Signals -- Chapter 4. Method of Envelope and Phase in the Tasks of Identification of Narrowband Noise Signals -- Chapter 5. Identification of Vibration Noise Signals of Electric Power Facilities -- Chapter 6. Examples of Stochastic Noise Signals Identification -- Chapter 7. Identification of Air Pollution Sources.The book meticulously details a constructive mathematical model of a stochastic noise process, specifically a linear random process and its characteristics. Theoretical reasoning on the relationship between random processes with independent increments and those with independent values, known as random processes of white noise, is provided. The model of a linear random process serves as a mathematical representation of colored noises in various hues. Characteristics of both non-stationary and stationary linear random processes are elucidated, with emphasis on their ergodic properties, crucial for practical applications. The study also encompasses the vector linear random process, portraying a model of multi-channel noise signals. A novel contribution to the theory of random functions is the development of a constructive model of a conditional linear random process. This involves determining its distribution laws in the form of a characteristic function and relevant statistical characteristics, which can serve as potential indicators for identifying stochastic noise processes. The book revisits research on periodic stochastic models, examining cyclic, rhythmic, natural, and artificial phenomena, processes, and signals. A comprehensive analysis of the linear periodic random process is conducted, and the identification characteristics of periodic models of stochastic noise signals are explored. Significant attention is directed toward employing contour and phase methods as a theoretical foundation for addressing narrow-band noise signal identification challenges.Studies in Systems, Decision and Control,2198-4190 ;567Electrical engineeringSignal processingNoise controlElectrical and Electronic EngineeringDigital and Analog Signal ProcessingNoise ControlElectrical engineering.Signal processing.Noise control.Electrical and Electronic Engineering.Digital and Analog Signal Processing.Noise Control.621.3Babak Vitalii1437507Zaporozhets Artur1437508Kuts Yurii1785708Fryz Mykhailo1785709Scherbak Leonid1785710MiAaPQMiAaPQMiAaPQBOOK9910983089003321Noise signals4317199UNINA