Cdex, Inc. (fka CDEX)

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ValiMed G4 image

United States Patent and Trademark Office

- thanks again to Paige

ValiMed G4 Medication Identificatin System Operating Manual

Case Id 85256767 Document Description
Specimen Mail/Create Date 03-Mar-2011

Note that page 2 states Since several spectroscopic methods are used
accuracy and specificity are greatly enhanced.
Note page 3 contents refer to ValiMed G4 Raman and Emmission Spectroscopy and Fast Fourier Transform

http://tdr.uspto.gov/jsp/DocumentViewPage.jsp?85256767/SPE20110307094017/Specimen/3/03-Mar-2011/sn/false#p=1

Fast Fourier transformFrom Wikipedia, the free encyclopedia

http://en.wikipedia.org/wiki/Fast_Fourier_transform

A fast Fourier transform (FFT) is an efficient algorithm to compute the discrete Fourier transform (DFT) and its inverse. "The FFT has been called the most important numerical algorithm of our lifetime (Strang, 1994)." (Kent & Read 2002, 61) There are many distinct FFT algorithms involving a wide range of mathematics, from simple complex-number arithmetic to group theory and number theory; this article gives an overview of the available techniques and some of their general properties, while the specific algorithms are described in subsidiary articles linked below.

A DFT decomposes a sequence of values into components of different frequencies. This operation is useful in many fields (see discrete Fourier transform for properties and applications of the transform) but computing it directly from the definition is often too slow to be practical. An FFT is a way to compute the same result more quickly: computing a DFT of N points in the naive way, using the definition, takes O(N2) arithmetical operations, while an FFT can compute the same result in only O(N log N) operations. The difference in speed can be substantial, especially for long data sets where N may be in the thousands or millions—in practice, the computation time can be reduced by several orders of magnitude in such cases, and the improvement is roughly proportional to N / log(N). This huge improvement made many DFT-based algorithms practical; FFTs are of great importance to a wide variety of applications, from digital signal processing and solving partial differential equations to algorithms for quick multiplication of large integers.

Raman spectroscopy

http://en.wikipedia.org/wiki/Raman_spectroscopy

Emission spectroscopy

http://en.wikipedia.org/wiki/Emission_Spectroscopy#Emission_spectroscopy