00902nam0-22003251i-450-99000049660040332120080403140100.00-201-17288-7000049660FED01000049660(Aleph)000049660FED0100004966020020821d1990----km-y0itay50------baengUSa-------001yyElectric circuitsJames W. Nilsson3rd ed.Reading, MassachusettsAddison-Wesley©1990829 p.ill.25 cm+ Manuale allegatoCircuiti elettrici621.319'2Nilsson,James W.<William ;1924- >9668ITUNINARICAUNIMARCBK99000049660040332110 C I 4161208 DEEDINELDINELElectric circuits177193UNINA01142nam a2200325 i 450099100134281970753620020507191730.0960223s1982 ne ||| | eng 0444862862b1083428x-39ule_instLE01310819ExLDip.to Matematicaeng514.24AMS 55P55QA612.7.S43Mardesic, Sibe55862Shape theory :the inverse system approach /S. Mardesic, J. SegalAmsterdam :North-Holland,1982xv, 378 p. :ill. ;23 cm.North-Holland mathematical library ;26Bibliography: p. 341-371.Includes indexShape theorySegal, Jackauthorhttp://id.loc.gov/vocabulary/relators/aut55051.b1083428x23-02-1728-06-02991001342819707536LE013 55P MAR11 (1982)12013000042626le013-E0.00-l- 00000.i1094364x28-06-02Shape theory3370783UNISALENTOle01301-01-96ma -engne 0102138nam 2200505 450 991027087710332120231010115139.01-119-27760-41-119-27759-01-119-27761-2(CKB)4330000000009889(MiAaPQ)EBC4835098(DLC) 2017005373(Au-PeEL)EBL4835098(CaPaEBR)ebr11368988(CaONFJC)MIL1004524(OCoLC)982019372(EXLCZ)99433000000000988920170419h20172017 uy 0engurcnu||||||||rdacontentrdamediardacarrierADA in details interpreting the 2010 Americans with Disabilities Act Standards for Accessible Design /Janis KentHoboken, New Jersey :Wiley,2017.©20171 online resource (299 pages) illustrations (some color)THEi Wiley ebooksIncludes index.1-119-27758-2 Includes bibliographical references and index.Integrate your designs with compliant access interpretations ADA in Details provides a visual interpretation of the 2010 Americans with Disabilities Act (ADA) Standards for a convenient, go-to reference of pertinent scoping, technical requirements, and sourcing information. Architects, designers, and everyone else involved in the built environment can turn to this authoritative resource to understand accessibility compliance for places of public accommodation, commercial facilities, and public buildings. Every detail is presented with both a clear explanation and illustrations that synthesize federal regulations and the 2016 California Building Code (CBC).THEi Wiley ebooks.Barrier-free designUnited StatesBarrier-free design720.87Kent Janis942029MiAaPQMiAaPQMiAaPQBOOK9910270877103321ADA in details2125477UNINA03674nam 2200505 450 991083055830332120231102015751.09781394209101(MiAaPQ)EBC30786527(CKB)28495742000041(Au-PeEL)EBL30786527(OCoLC)1404054997(OCoLC-P)1404054997(CaSebORM)9781394209088(EXLCZ)992849574200004120231102d2024 uy 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierMachine and Deep Learning Using MATLAB Algorithms and Tools for Scientists and Engineers /Kamal I. M. Al-MalahFirst edition.Hoboken, NJ :John Wiley & Sons, Inc.,[2024]©20241 online resource (965 pages)Includes index.9781394209088 MACHINE AND DEEP LEARNING In-depth resource covering machine and deep learning methods using MATLAB tools and algorithms, providing insights and algorithmic decision-making processes Machine and Deep Learning Using MATLAB introduces early career professionals to the power of MATLAB to explore machine and deep learning applications by explaining the relevant MATLAB tool or app and how it is used for a given method or a collection of methods. Its properties, in terms of input and output arguments, are explained, the limitations or applicability is indicated via an accompanied text or a table, and a complete running example is shown with all needed MATLAB command prompt code. The text also presents the results, in the form of figures or tables, in parallel with the given MATLAB code, and the MATLAB written code can be later used as a template for trying to solve new cases or datasets. Throughout, the text features worked examples in each chapter for self-study with an accompanying website providing solutions and coding samples. Highlighted notes draw the attention of the user to critical points or issues. Readers will also find information on: Numeric data acquisition and analysis in the form of applying computational algorithms to predict the numeric data patterns (clustering or unsupervised learning) Relationships between predictors and response variable (supervised), categorically sub-divided into classification (discrete response) and regression (continuous response) Image acquisition and analysis in the form of applying one of neural networks, and estimating net accuracy, net loss, and/or RMSE for the successive training, validation, and testing steps Retraining and creation for image labeling, object identification, regression classification, and text recognition Machine and Deep Learning Using MATLAB is a useful and highly comprehensive resource on the subject for professionals, advanced students, and researchers who have some familiarity with MATLAB and are situated in engineering and scientific fields, who wish to gain mastery over the software and its numerous applications.Machine learningNumerical analysisData processingComputer programmingNumerical analysisComputer programsMachine learning.Numerical analysisData processing.Computer programming.Numerical analysisComputer programs.001.642Al-Malah Kamal I. M.1646649MiAaPQMiAaPQMiAaPQ9910830558303321Machine and Deep Learning Using MATLAB3993757UNINA