Parameter Space Calculus Parametric (2 results)

Title
Refine with Advanced Search

Refine your search

  • Books (2)

  • New (2)

to

Custom price range (US$)

to

  • Language: English

    Published by OmniScriptum, 2026

    6131261113 / 9786131261114

    • Softcover
    • Print on Demand

    Seller: preigu, Osnabrück, Germanypreigu

    5-star seller
    Contact seller

    Condition: New

    US$ 111.68

    US$ 80.40 shipping 
    Ships from Germany to U.S.A.

    Quantity: 5 available

    Taschenbuch. Condition: Neu. Parameter Space | Calculus, Parametric Array, Transducer, Sound Wave, Diffraction Limit | Lambert M. Surhone (u. a.) | Taschenbuch | Englisch | 2026 | OmniScriptum | EAN 9786131261114 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu Print on Demand.

  • Language: English

    Published by Omniscriptum, 2026

    6131261113 / 9786131261114

    • Softcover
    • Print on Demand

    Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH

    5-star seller
    Contact seller

    Condition: New

    US$ 192.10

    US$ 35.03 shipping 
    Ships from Germany to U.S.A.

    Quantity: 1 available

    Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. The term parameter space as used in data-fitting (see for example 'Data Reduction and Error Analysis for the Physical Sciences' by Bevington and Robinson), refers to the hypothetical space where a 'location' is defined by the values of all optimizable parameters. For example, if we fit data using a function which has 10 optimizable parameters, each of these parameters is seen as a dimension and the parameter space in this case is 10-dimensional. Every 'location' then corresponds to a (chi-squared) value indicating the goodness-of-fit, hence we have a 'field' in our 10-dimensional space. Following this 'field' downwards leads us to the 'location' in parameter space with the lowest , i.e. the optimum parameter values.