EFFECT OF CRYSTAL-FIELD AND BONDING PROPERTIES ON SPECTRAL STRUCTURE OF EU-2+

Five Eu~(2+)-doped simple fluorides and six Eu~(2+)-doped complex fluorides are synthesized by solid reactions. The strength of the crystal-field at the sites of Eu~(2+) ion, and the degroe of covalenco of Eu—F bond in these hosts are discussed. The f-f transition emission of Eu~(2+) ion is observed in the hosts which has lower coordination number and strong crystal-field. The f-f transition emission of Eu~(2+) ion is observed for the first time in the simple fluoride AlF_3.

Spectral changes of C-phycocyanin with different molar ratios of SPDP

Pure C-phycocyanin was prepared from Spirulina platensis using one-step anion-exchange chromatography. The C-PC obtained was with an absorption maximum at 620 nm and a fluorescence emission maximum at 640 nm when excited by 580 nm. SPDP is an excellent heterobifunctional crosslinker for thiolating amines. Different molar ratios of SPDP have remarkable influence on the absorption and fluorescence spectra of C-phycocyanin. The absorption maximum and fluorescence emission maximum both decreased and blue-shifted from 640 run to 630 nm as the molar ratios of SPDP increased. It was found that the molar ratios of SPDP to C-phycocyanin was not more than 100 was appropriate to being conjugated with other biomolecules from the absorption and fluorescence spectra of C-phycocyanin.

Template Matching: Matched Spatial Filters and Beyond

Template matching by means of cross-correlation is common practice in pattern recognition. However, its sensitivity to deformations of the pattern and the broad and unsharp peaks it produces are significant drawbacks. This paper reviews some results on how these shortcomings can be removed. Several techniques (Matched Spatial Filters, Synthetic Discriminant Functions, Principal Components Projections and Reconstruction Residuals) are reviewed and compared on a common task: locating eyes in a database of faces. New variants are also proposed and compared: least squares Discriminant Functions and the combined use of projections on eigenfunctions and the corresponding reconstruction residuals. Finally, approximation networks are introduced in an attempt to improve filter design by the introduction of nonlinearity.

Adaptive denoising in spectral analysis by genetic programming

Rowland, J.J. and Taylor, J. (2002). Adaptive denoising in spectral analysis by genetic programming. Proc. IEEE Congress on Evolutionary Computation (part of WCCI), May 2002. pp 133-138. ISBN 0-7803-7281-6

A review of spectral properties of plants and their potential use for crop/weed discrimination in row-crops

R. Zwiggelaar, 'A review of spectral properties of plants and their potential use for crop/weed discrimination in row-crops', Crop Protection 17 (3), 189-206 (1998)

Spectral changes in inhomogeneous media : a quasi-optical approach

R. Zwiggelaar and M.G.F. Wilson, 'Spectral changes in inhomogeneous media; a quasi-optical approach', Int. J. Infrared Millimeter Waves 14 (10), 2253-2259 (1993)

Validation of a parabolic trough solar receiver model based on physical formulation of the absorber total emissivity from its spectral emissivity

Concentrating solar power is an important way of providing renewable energy. Model simulation approaches play a fundamental role in the development of this technology and, for this, an accurately validation of the models is crucial. This work presents the validation of the heat loss model of the absorber tube of a parabolic trough plant by comparing the model heat loss estimates with real measurements in a specialized testing laboratory. The study focuses on the implementation in the model of a physical-meaningful and widely valid formulation of the absorber total emissivity depending on the surface’s temperature. For this purpose, the spectral emissivity of several absorber’s samples are measured and, with these data, the absorber total emissivity curve is obtained according to Planck function. This physical-meaningful formulation is used as input parameter in the heat loss model and a successful validation of the model is performed. Since measuring the spectral emissivity of the absorber surface may be complex and it is sample-destructive, a new methodology for the absorber’s emissivity characterization is proposed. This methodology provides an estimation of the absorber total emissivity, retaining its physical meaning and widely valid formulation according to Planck function with no need for direct spectral measurements. This proposed method is also successfully validated and the results are shown in the present paper.

AIRSTREAM: A Neural Network Model of Auditory Scene Analysis and Source Segregation

Multiple sound sources often contain harmonics that overlap and may be degraded by environmental noise. The auditory system is capable of teasing apart these sources into distinct mental objects, or streams. Such an "auditory scene analysis" enables the brain to solve the cocktail party problem. A neural network model of auditory scene analysis, called the AIRSTREAM model, is presented to propose how the brain accomplishes this feat. The model clarifies how the frequency components that correspond to a give acoustic source may be coherently grouped together into distinct streams based on pitch and spatial cues. The model also clarifies how multiple streams may be distinguishes and seperated by the brain. Streams are formed as spectral-pitch resonances that emerge through feedback interactions between frequency-specific spectral representaion of a sound source and its pitch. First, the model transforms a sound into a spatial pattern of frequency-specific activation across a spectral stream layer. The sound has multiple parallel representations at this layer. A sound's spectral representation activates a bottom-up filter that is sensitive to harmonics of the sound's pitch. The filter activates a pitch category which, in turn, activate a top-down expectation that allows one voice or instrument to be tracked through a noisy multiple source environment. Spectral components are suppressed if they do not match harmonics of the top-down expectation that is read-out by the selected pitch, thereby allowing another stream to capture these components, as in the "old-plus-new-heuristic" of Bregman. Multiple simultaneously occuring spectral-pitch resonances can hereby emerge. These resonance and matching mechanisms are specialized versions of Adaptive Resonance Theory, or ART, which clarifies how pitch representations can self-organize durin learning of harmonic bottom-up filters and top-down expectations. The model also clarifies how spatial location cues can help to disambiguate two sources with similar spectral cures. Data are simulated from psychophysical grouping experiments, such as how a tone sweeping upwards in frequency creates a bounce percept by grouping with a downward sweeping tone due to proximity in frequency, even if noise replaces the tones at their interection point. Illusory auditory percepts are also simulated, such as the auditory continuity illusion of a tone continuing through a noise burst even if the tone is not present during the noise, and the scale illusion of Deutsch whereby downward and upward scales presented alternately to the two ears are regrouped based on frequency proximity, leading to a bounce percept. Since related sorts of resonances have been used to quantitatively simulate psychophysical data about speech perception, the model strengthens the hypothesis the ART-like mechanisms are used at multiple levels of the auditory system. Proposals for developing the model to explain more complex streaming data are also provided.

A Spectral Network Model of Pitch Perception

A model of pitch perception, called the Spatial Pitch Network or SPINET model, is developed and analyzed. The model neurally instantiates ideas front the spectral pitch modeling literature and joins them to basic neural network signal processing designs to simulate a broader range of perceptual pitch data than previous spectral models. The components of the model arc interpreted as peripheral mechanical and neural processing stages, which arc capable of being incorporated into a larger network architecture for separating multiple sound sources in the environment. The core of the new model transforms a spectral representation of an acoustic source into a spatial distribution of pitch strengths. The SPINET model uses a weighted "harmonic sieve" whereby the strength of activation of a given pitch depends upon a weighted sum of narrow regions around the harmonics of the nominal pitch value, and higher harmonics contribute less to a pitch than lower ones. Suitably chosen harmonic weighting functions enable computer simulations of pitch perception data involving mistuned components, shifted harmonics, and various types of continuous spectra including rippled noise. It is shown how the weighting functions produce the dominance region, how they lead to octave shifts of pitch in response to ambiguous stimuli, and how they lead to a pitch region in response to the octave-spaced Shepard tone complexes and Deutsch tritones without the use of attentional mechanisms to limit pitch choices. An on-center off-surround network in the model helps to produce noise suppression, partial masking and edge pitch. Finally, it is shown how peripheral filtering and short term energy measurements produce a model pitch estimate that is sensitive to certain component phase relationships.