✦ LIBER ✦

Handbook of Vibrational Spectroscopy || Inverse Least Squares and Classical Least Squares Methods for Quantitative Vibrational Spectroscopy

✍ Scribed by Chalmers, John M.; Griffiths, Peter R.

Book ID: 127341326
Publisher: John Wiley & Sons, Ltd
Year: 2006
Weight: 185 KB
Category: Article
ISBN-13: 9780470027325
DOI: 10.1002/0470027320.s4603

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

Multi-window Classical Least-Squares Mul

Multi-window Classical Least-Squares Multivariate Calibration Methods for Quantitative ICP-AES Analyses

✍ Haaland, David M.; Chambers, William B.; Keenan, Michael R.; Melgaard, David K. 📂 Article 📅 2000 🏛 Society for Applied Spectroscopy 🌐 English ⚖ 314 KB

Vibrational spectroscopy coupled to clas

Vibrational spectroscopy coupled to classical least square analysis, a new approach for determination of skin moisturizing agents' mechanisms

✍ Vyumvuhore, R.; Tfayli, A.; Manfait, M.; Baillet-Guffroy, A. 📂 Article 📅 2013 🏛 John Wiley and Sons 🌐 English ⚖ 403 KB

Solution of an inverse vibration problem

Solution of an inverse vibration problem using a linear least-squares error method

✍ Yang Ching-Yu 📂 Article 📅 1996 🏛 Elsevier Science 🌐 English ⚖ 419 KB

Moving Least-Squares Differential Quadra

Moving Least-Squares Differential Quadrature Method for Free Vibration of Antisymmetric Laminates

✍ Li, Q. S.; Huang, Y. Q. 📂 Article 📅 2004 🏛 American Society of Civil Engineers 🌐 English ⚖ 128 KB

Classical univariate calibration and par

Classical univariate calibration and partial least squares for quantitative analysis of brass samples by laser-induced breakdown spectroscopy

✍ Jose Manuel Andrade; Gabriele Cristoforetti; Stefano Legnaioli; Giulia Lorenzett 📂 Article 📅 2010 🏛 Elsevier Science 🌐 English ⚖ 875 KB

New Prediction-Augmented Classical Least

New Prediction-Augmented Classical Least-Squares (PACLS) Methods: Application to Unmodeled Interferents

✍ Haaland, David M.; Melgaard, David K. 📂 Article 📅 2000 🏛 Society for Applied Spectroscopy 🌐 English ⚖ 347 KB