Signal processing basics

Continuous Measurements In most apphcations, continuous measurements are considerably more ambitious than discrete measurements. Basically, discrete measurements involve a yes/no decision, whereas continuous measurements may entail considerable signal processing. 

The most versatile data acquisition option is a stand alone data collection unit. At Glidden we use an Elexor Data Logger (S) for this purpose. It has its own microprocessor and BASIC Interpreter and communicates with the computer via the serial port. The unit can be configured with a wide variety of signal processing options. 

SOXAL A flue-gas desulfurization process, basically similar to the Wellman-Lord process but regenerating the bisulfite solution in a membrane electrochemical cell. Developed by Allied Signal Group and piloted at the Florida Power Light Company, Miami, FL, in 1991. A larger demonstration plant was planned for Dunkirk, New York. 

What are the six basic elements of a mass spectrometer (sample introduction, ion source, mass analyzer, detector, signal processing and computer). 

The basic system is designed to function as an information-processing unit that receives an input signal, processes it through a specific function, and produces the output signal. 

Neutron or y Sensors Neutron- or y -based sensors are similar in concept to the X-ray sensors. They use different forms of excitation and different detectors, but the basic forms of transmission or backscatter follow the pattern described above. Both normally rely on extensive computation for signal processing called computed tomography, where the detector signals are combined to synthesize an image of the irradiated object. 

Arachidonic acid is the biosynthetic precursor of metabolites (such as prostaglandins) that play a basic role in cell signal processes. Fluorine atoms have been introduced on the strategic oxidation sites of arachidonic acid in order to study the... 

In this review, a critical overview of artificial tongue applications over the last decade is outlined. In particular, the focus is centered on the chemometric techniques, which allow the extraction of valuable information from nonspecific data. The basic steps of signal processing and pattern recognition are discussed and the principal chemometric techniques are described in detail, highlighting benefits and drawbacks of each one. Furthermore, some novel methods recently introduced and particularly suitable for artificial tongue data are presented. 

In the following we will deal with the basic components and principles of intracellular signal transduction and signal processing. The specific reactions and levels of signal transduction will be dealt with in detail in later chapters. 

In order to maximize information obtained from raw spectroscopic data, analytical chemists and instrumental specialists depend an signal processing and apply a large number of specialized versions of the basic methods considered in this chapter, as well as the parametric methods discussed in the previous chapter, see, e.g. (ref. 22). Here we provide only an example of parametric methods. Table 4.4 shows 20 points of the electronic absorption spectrum of o-phenilenediamidine in ethanol (ref. 23). 

Evans, D.H, and N. McDicken Doppler Ultrasound Physics, Instrumentation, and Signal Processing. 2nd Edition. John Wiley Sons, Inc., New York. NY, 2000 Harness. J.K. Ultrasound in Surgical Practice Basic Principles and Clinical Applications, John Wiley Sons, Inc., New York, NY, 1999. 

T.F. Quatieri and R.J. McAulay Audio Signal Processing Based on Sinusoidal Analysis/Synthesis. One of the basic paradigms of digital audio analysis, coding (i.e. analysis/synthesis) and synthesis systems is the sinusoidal model. It has been used for many systems from speech coding to music synthesis. The chapter contains the unified view of both the basics of sinusoidal analysis/synthesis and some of the applications. 

The next step is to apply the basic principles of information theory, signal processing theory, multivariate data interpretation, and adaptive instrumental control in order to enhance and effectively extract information. 

A typical Raman system consists of the following basic components (1) an excitation source, usually a laser (2) optics for sample illumination (3) a double or triple monochromator and (4) a signal processing system consisting of a detector, an amplifier, and an output device. A diagram showing various components of the Raman spectrometer is shown in Fig. 4.6.2. 

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