Photoacoustic signal saturation and optical limiting in C70-toluene solution

Pulsed photoacoustic studies in solutions of C70 in toluene are made using the 532-nm radiation from a frequency-doubled Nd:YAG laser. It is found that contrary to expectation, there is no photoacoustic (PA) signal enhancement in the power-limiting range of laser fluences. Instead, the PA signal tends to saturate during optical power-limiting phenomenon. This could be due to the enhanced optical absorption from the photoexcited state and hence the depletion of the ground-state population. PA measurements also ruled out the possibility of multiphoton absorption in the C70 solution. We demonstrate that the nonlinear absorption leading to optical limiting is mainly due to reverse saturable absorption.

Permutation entropy based real-time chatter detection using audio signal in turning process

Machine tool chatter is an unfavorable phenomenon during metal cutting, which results in heavy vibration of cutting tool. With increase in depth of cut, the cutting regime changes from chatter-free cutting to one with chatter. In this paper, we propose the use of permutation entropy (PE), a conceptually simple and computationally fast measurement to detect the onset of chatter from the time series using sound signal recorded with a unidirectional microphone. PE can efficiently distinguish the regular and complex nature of any signal and extract information about the dynamics of the process by indicating sudden change in its value. Under situations where the data sets are huge and there is no time for preprocessing and fine-tuning, PE can effectively detect dynamical changes of the system. This makes PE an ideal choice for online detection of chatter, which is not possible with other conventional nonlinear methods. In the present study, the variation of PE under two cutting conditions is analyzed. Abrupt variation in the value of PE with increase in depth of cut indicates the onset of chatter vibrations. The results are verified using frequency spectra of the signals and the nonlinear measure, normalized coarse-grained information rate (NCIR).

Statistical signal extraction using stable processes

The standard models for statistical signal extraction assume that the signal and noise are generated by linear Gaussian processes. The optimum filter weights for those models are derived using the method of minimum mean square error. In the present work we study the properties of signal extraction models under the assumption that signal/noise are generated by symmetric stable processes. The optimum filter is obtained by the method of minimum dispersion. The performance of the new filter is compared with their Gaussian counterparts by simulation.

" Nonlinear Signal Processing of Electroencephalogram .' Application in the Study of Neurodynamics. "

Interfacings of various subjects generate new field ofstudy and research that help in advancing human knowledge. One of the latest of such fields is Neurotechnology, which is an effective amalgamation of neuroscience, physics, biomedical engineering and computational methods. Neurotechnology provides a platform to interact physicist; neurologist and engineers to break methodology and terminology related barriers. Advancements in Computational capability, wider scope of applications in nonlinear dynamics and chaos in complex systems enhanced study of neurodynamics. However there is a need for an effective dialogue among physicists, neurologists and engineers. Application of computer based technology in the field of medicine through signal and image processing, creation of clinical databases for helping clinicians etc are widely acknowledged. Such synergic effects between widely separated disciplines may help in enhancing the effectiveness of existing diagnostic methods. One of the recent methods in this direction is analysis of electroencephalogram with the help of methods in nonlinear dynamics. This thesis is an effort to understand the functional aspects of human brain by studying electroencephalogram. The algorithms and other related methods developed in the present work can be interfaced with a digital EEG machine to unfold the information hidden in the signal. Ultimately this can be used as a diagnostic tool.

Large-Size AlGaN/GaN HEMT Large-Signal Electrothermal Characterization and Modeling for Wireless Digital Communications

The rapid growth in high data rate communication systems has introduced new high spectral efficient modulation techniques and standards such as LTE-A (long term evolution-advanced) for 4G (4th generation) systems. These techniques have provided a broader bandwidth but introduced high peak-to-average power ratio (PAR) problem at the high power amplifier (HPA) level of the communication system base transceiver station (BTS). To avoid spectral spreading due to high PAR, stringent requirement on linearity is needed which brings the HPA to operate at large back-off power at the expense of power efficiency. Consequently, high power devices are fundamental in HPAs for high linearity and efficiency. Recent development in wide bandgap power devices, in particular AlGaN/GaN HEMT, has offered higher power level with superior linearity-efficiency trade-off in microwaves communication. For cost-effective HPA design to production cycle, rigorous computer aided design (CAD) AlGaN/GaN HEMT models are essential to reflect real response with increasing power level and channel temperature. Therefore, large-size AlGaN/GaN HEMT large-signal electrothermal modeling procedure is proposed. The HEMT structure analysis, characterization, data processing, model extraction and model implementation phases have been covered in this thesis including trapping and self-heating dispersion accounting for nonlinear drain current collapse. The small-signal model is extracted using the 22-element modeling procedure developed in our department. The intrinsic large-signal model is deeply investigated in conjunction with linearity prediction. The accuracy of the nonlinear drain current has been enhanced through several issues such as trapping and self-heating characterization. Also, the HEMT structure thermal profile has been investigated and corresponding thermal resistance has been extracted through thermal simulation and chuck-controlled temperature pulsed I(V) and static DC measurements. Higher-order equivalent thermal model is extracted and implemented in the HEMT large-signal model to accurately estimate instantaneous channel temperature. Moreover, trapping and self-heating transients has been characterized through transient measurements. The obtained time constants are represented by equivalent sub-circuits and integrated in the nonlinear drain current implementation to account for complex communication signals dynamic prediction. The obtained verification of this table-based large-size large-signal electrothermal model implementation has illustrated high accuracy in terms of output power, gain, efficiency and nonlinearity prediction with respect to standard large-signal test signals.

Electrophysiological analysis of the olfactory signal transduction cascade in the hawkmoth Manduca sexta

Neben der Verbreitung von gefährlichen Krankheiten sind Insekten für enorme agrarwirtschaftliche Schäden verantwortlich. Ein Großteil der Verhaltensweisen bei Insekten wird über den Geruchssinn gesteuert, der somit einen möglichen Angriffspunkt zur Bekämpfung von Schadinsekten darstellt. Hierzu ist es allerdings nötig, die Mechanismen der olfaktorischen Signalübertragung im Detail zu verstehen. Neben den duftstoffbindenden olfaktorischen Rezeptoren spielt hier auch ein konservierter Korezeptor (Orco) eine entscheidende Rolle. Inwieweit bei diesen Proteinen ionotrope bzw. metabotrope Prozesse involviert sind ist bislang nicht vollständig aufgeklärt. Um weitere Einzelheiten aufzuklären wurden daher Einzelsensillenableitungen am Tabakschwärmer Manduca sexta durchgeführt. Orco-Agonisten und Antagonisten wurden eingesetzt, um die Funktion des Korezeptors besser zu verstehen. Bei dem Einsatz des Orco-Agonisten VUAA1 konnte keine Verstärkung der Pheromonantworten bzw. eine Sensitivierung beobachtet werden, wie im Falle einer ionotropen Signalweiterleitung zu erwarten gewesen wäre. Ein ionotroper Signalweg über den OR/Orco-Komplex in M. sexta ist daher unwahrscheinlich. Der Orco-Antagonist OLC15 beeinflusste die gleichen Parameter wie VUAA1 und konnte die von VUAA1 generierte Spontanaktivität blocken. Daher ist es wahrscheinlich, dass dieser einen spezifischen Orco-Blocker darstellt. Sowohl VUAA1 als auch OLC15 hatten großen Effekt auf die langanhaltende Pheromonantwort, welches die Vermutung nahelegt, dass Orco modulierend auf die Sensitivität der Nervenzelle einwirkt. Von OLC15 abweichende Effekte durch die getesteten Amiloride HMA und MIA auf die Pheromonantwort lassen nicht auf eine spezifische Wirkung dieser Agenzien auf Orco schließen und zusätzliche Wirkorte sind anzunehmen. Um die These eines metabotropen Signalwegs zu überprüfen wurde ebenfalls der G-Protein-Blocker GDP-β-S eingesetzt. Alle Parameter der Pheromonantwort die innerhalb der ersten Millisekunden analysiert wurden wiesen eine Reduktion der Sensitivität auf. Im Gegensatz dazu hatte GDP-β-S keinen Effekt auf die langanhaltende Pheromonantwort. Somit scheint ausschließlich die schnelle Pheromonantwort über einen Ligand-bindenden G-Protein-gesteuerten Rezeptor gesteuert zu werden.

A Vector Signal Processing Approach to Color

Surface (Lambertain) color is a useful visual cue for analyzing material composition of scenes. This thesis adopts a signal processing approach to color vision. It represents color images as fields of 3D vectors, from which we extract region and boundary information. The first problem we face is one of secondary imaging effects that makes image color different from surface color. We demonstrate a simple but effective polarization based technique that corrects for these effects. We then propose a systematic approach of scalarizing color, that allows us to augment classical image processing tools and concepts for multi-dimensional color signals.

Using crises, feedback, and fading for online task design

Resumen basado en el de la publicaci??n

Signal processing of microstructure profiles: integrating turbulent spatial scales in aquatic ecological modeling

The main objective of this thesis was the integration of microstructure information in synoptic descriptors of turbulence, that reflects the mixing processes. Turbulent patches are intermittent in space and time, but they represent the dominant process for mixing. In this work, the properties of turbulent patches were considered the potential input for integrating the physical microscale measurements. The development of a method for integrating the properties of the turbulent patches required solving three main questions: a) how can we detect the turbulent patches from he microstructure measurements?; b) which are the most relevant properties of the turbulent patches?; and ) once an interval of time has been selected, what kind of synoptic parameters could better reflect the occurrence and properties of the turbulent patches? The answers to these questions were the final specific objectives of this thesis.

Are distortion levels a problem with digital signal processing hearing aids and frequency modulation (FM) systems?

The purpose of this study was to examine objective and subjective distortion present when frequency modulation (FM) systems were coupled with four digital signal processing (DSP) hearing aids. Electroacoustic analysis and subjective listening tests by experienced audiologists revealed that distortion levels varied across hearing aids and channels.

Compensatory signal processing for profoundly hearing-impaired listeners: the transmission of fundamental frequency

This paper reviews a study to determine the usefulness of signal processing along with lipreading in improving speech perception of profoundly hearing impaired persons.