Phase-Locked Loop design applied to frequency-modulated atomic force microscope

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

A phase-shifting control for variable frequency multi-cells interleaved boost pre-regulator based on FPGA device

In this paper were investigated phase-shift control strategies applied to a four cells interleaved high input-power-factor pre-regulator boost rectifier, operating in critical conduction mode, using a non-dissipative commutation cells and frequency modulation. The digital control has been developed using a hardware description language (VHDL) and implemented using the XC2S200E-SpartanII-E/Xilinx FPGA, performing a true critical conduction operation mode for a generic number of interleaved cells. Experimental results are presented, in order to verify the feasibility and performance of the proposed digital control, through the use of a Xilinx FPGA device.

Loss of sleep spindle frequency deceleration in Obstructive Sleep Apnea

Objective: Sleep spindles have been suggested as surrogates of thalamo-cortical activity. Internal frequency modulation within a spindle's time frame has been demonstrated in healthy subjects, showing that spindles tend to decelerate their frequency before termination. We investigated internal frequency modulation of slow and fast spindles according to Obstructive Sleep Apnea (OSA) severity and brain topography. Methods: Seven non-OSA subjects and 21 patients with OSA contributed with 30 min of Non-REM sleep stage 2, subjected to a Matching pursuit procedure with Gabor chirplet functions for automatic detection of sleep spindles and quantification of sleep spindle internal frequency modulation (chirp rate). Results: Moderate OSA patients showed an inferior percentage of slow spindles with deceleration when compared to Mild and Non-OSA groups in frontal and parietal regions. In parietal regions, the percentage of slow spindles with deceleration was negatively correlated with global apnea-hypopnea index (r s = -0.519, p = 0.005). Discussion: Loss of physiological sleep spindle deceleration may either represent a disruption of thalamo-cortical loops generating spindle oscillations or some compensatory mechanism, an interesting venue for future research in the context of cognitive dysfunction in OSA. Significance: Quantification of internal frequency modulation (chirp rate) is proposed as a promising approach to advance description of sleep spindle dynamics in brain pathology. © 2013 International Federation of Clinical Neurophysiology.

A standard for RF modulation factor /

Report No. FAA-RD-79-94." Microfiche.

Direct support and general support maintenance repair parts and special tools list for receiver, radio frequency, Weinschel, model VM-4A, NSN 4931-01-041-1564 and tracking oscillator, Weinschel, model VM-4A/H0-2, NSN 6695-01-102-4342.

Includes index.

A high-power-factor, three-phase isolated AC-DC converter using high-frequency current injection

A single-stage, three-phase AC-to-DC converter topology is proposed for high-frequency power supply applications. The principal features of the circuit include continuous current operation of the three AC input inductors, inherent shaping of the input currents, resulting in high power factor, a transformer isolated output, and only two active devices are required, both soft-switched. Resonant conversion techniques are used, and a high power factor is achieved by injecting high-frequency currents into the three-phase rectifier, producing a high frequency modulation of the rectifier input voltages. The current injection principle is explained and the system operation is confirmed by a combination of simulation and experimental results.

Functional connectivity of gamma EEG activity is modulated at low frequency during conscious recollection

We examined two subjectively distinct memory states that are elicited during recognition memory in humans and compared them in terms of the gamma oscillations (20–60 Hz) in the electroencepahalogram (EEG) that they induced. These subjective states, ‘recollection’ and ‘familiarity’ both entail correct recognition but one involves a clear and conscious recollection of the event including memory for contextual detail whilst the other involves a sense of familiarity without clear recollection. Here we show that during a verbal recognition memory test, the subjective experience of ‘recollection’ induced higher amplitude gamma oscillations than the subjective experience of ‘familiarity’ in the time period 300–500 ms after stimulus presentation. Recollection, but not familiarity, was also associated with greater functional connectivity in the gamma frequency range between frontal and parietal sites. Furthermore, the magnitude of the gamma functional connectivity varied over time and was modulated at 3 Hz. Previous studies in animals have shown local theta frequency modulation (3–7 Hz) of gamma-oscillations but this is the first time that a similar effect has been reported in the human EEG.

Sparse time-frequency data analysis : a multi-scale approach

In this work, we further extend the recently developed adaptive data analysis method, the Sparse Time-Frequency Representation (STFR) method. This method is based on the assumption that many physical signals inherently contain AM-FM representations. We propose a sparse optimization method to extract the AM-FM representations of such signals. We prove the convergence of the method for periodic signals under certain assumptions and provide practical algorithms specifically for the non-periodic STFR, which extends the method to tackle problems that former STFR methods could not handle, including stability to noise and non-periodic data analysis. This is a significant improvement since many adaptive and non-adaptive signal processing methods are not fully capable of handling non-periodic signals. Moreover, we propose a new STFR algorithm to study intrawave signals with strong frequency modulation and analyze the convergence of this new algorithm for periodic signals. Such signals have previously remained a bottleneck for all signal processing methods. Furthermore, we propose a modified version of STFR that facilitates the extraction of intrawaves that have overlaping frequency content. We show that the STFR methods can be applied to the realm of dynamical systems and cardiovascular signals. In particular, we present a simplified and modified version of the STFR algorithm that is potentially useful for the diagnosis of some cardiovascular diseases. We further explain some preliminary work on the nature of Intrinsic Mode Functions (IMFs) and how they can have different representations in different phase coordinates. This analysis shows that the uncertainty principle is fundamental to all oscillating signals.

Acoustic classification of Australian anurans using syllable features

Acoustic classification of anurans (frogs) has received increasing attention for its promising application in biological and environment studies. In this study, a novel feature extraction method for frog call classification is presented based on the analysis of spectrograms. The frog calls are first automatically segmented into syllables. Then, spectral peak tracks are extracted to separate desired signal (frog calls) from background noise. The spectral peak tracks are used to extract various syllable features, including: syllable duration, dominant frequency, oscillation rate, frequency modulation, and energy modulation. Finally, a k-nearest neighbor classifier is used for classifying frog calls based on the results of principal component analysis. The experiment results show that syllable features can achieve an average classification accuracy of 90.5% which outperforms Mel-frequency cepstral coefficients features (79.0%).

Vocalizations of wild Asian elephants (Elephas maximus): Structural classification and social context

Elephants use vocalizations for both long and short distance communication. Whereas the acoustic repertoire of the African elephant (Loxodonta africana) has been extensively studied in its savannah habitat, very little is known about the structure and social context of the vocalizations of the Asian elephant (Elephas maximus), which is mostly found in forests. In this study, the vocal repertoire of wild Asian elephants in southern India was examined. The calls could be classified into four mutually exclusive categories, namely, trumpets, chirps, roars, and rumbles, based on quantitative analyses of their spectral and temporal features. One of the call types, the rumble, exhibited high structural diversity, particularly in the direction and extent of frequency modulation of calls. Juveniles produced three of the four call types, including trumpets, roars, and rumbles, in the context of play and distress. Adults produced trumpets and roars in the context of disturbance, aggression, and play. Chirps were typically produced in situations of confusion and alarm. Rumbles were used for contact calling within and among herds, by matriarchs to assemble the herd, in close-range social interactions, and during disturbance and aggression. Spectral and temporal features of the four call types were similar between Asian and African elephants.

Comparison of AM-FM Based Features For Robust Speech Recognition

Effective feature extraction for robust speech recognition is a widely addressed topic and currently there is much effort to invoke non-stationary signal models instead of quasi-stationary signal models leading to standard features such as LPC or MFCC. Joint amplitude modulation and frequency modulation (AM-FM) is a classical non-parametric approach to non-stationary signal modeling and recently new feature sets for automatic speech recognition (ASR) have been derived based on a multi-band AM-FM representation of the signal. We consider several of these representations and compare their performances for robust speech recognition in noise, using the AURORA-2 database. We show that FEPSTRUM representation proposed is more effective than others. We also propose an improvement to FEPSTRUM based on the Teager energy operator (TEO) and show that it can selectively outperform even FEPSTRUM

0.84 ps Resolution Clock Skew Measurement via Subsampling

An all-digital on-chip clock skew measurement system via subsampling is presented. The clock nodes are sub-sampled with a near-frequency asynchronous sampling clock to result in beat signals which are themselves skewed in the same proportion but on a larger time scale. The beat signals are then suitably masked to extract only the skews of the rising edges of the clock signals. We propose a histogram of the arithmetic difference of the beat signals which decouples the relationship of clock jitter to the minimum measurable skew, and allows skews arbitrarily close to zero to be measured with a precision limited largely by measurement time, unlike the conventional XOR based histogram approach. We also analytically show that the proposed approach leads to an unbiased estimate of skew. The measured results from a 65 nm delay measurement front-end indicate that for an input skew range of +/- 1 fan-out-of-4 (FO4) delay, +/- 3 sigma resolution of 0.84 ps can be obtained with an integral error of 0.65 ps. We also experimentally demonstrate that a frequency modulation on a sampling clock maintains precision, indicating the robustness of the technique to jitter. We also show how FM modulation helps in restoring precision in case of rationally related clocks.

A mixture model approach for formant tracking and the robustness of student's-t distribution

We address the problem of robust formant tracking in continuous speech in the presence of additive noise. We propose a new approach based on mixture modeling of the formant contours. Our approach consists of two main steps: (i) Computation of a pyknogram based on multiband amplitude-modulation/frequency-modulation (AM/FM) decomposition of the input speech; and (ii) Statistical modeling of the pyknogram using mixture models. We experiment with both Gaussian mixture model (GMM) and Student's-t mixture model (tMM) and show that the latter is robust with respect to handling outliers in the pyknogram data, parameter selection, accuracy, and smoothness of the estimated formant contours. Experimental results on simulated data as well as noisy speech data show that the proposed tMM-based approach is also robust to additive noise. We present performance comparisons with a recently developed adaptive filterbank technique proposed in the literature and the classical Burg's spectral estimator technique, which show that the proposed technique is more robust to noise.

Temperature dependence of spin lifetime of conduction electrons in bulk germanium

Optically generated spin polarized electrons in bulk n-type Ge samples have been detected by using a radio-frequency modulation technique. Using the Hanle effect in an external magnetic field, the spin lifetime was measured as a function of temperature in the range 90 K to 180 K. The lifetime decreases with increasing temperature from similar to 5 ns at 100 K to similar to 2 ns at 180 K. We show that the temperature dependence is consistent with the Elliott-Yafet spin relaxation mechanism R. J. Elliot, Phys. Rev. 96, 266 (1954)]. (C) 2012 American Institute of Physics. http://dx.doi.org/10.1063/1.4772500]

Study of Multilevel Sinusoidal PWM methods for Cascaded H-Bridge Multilevel Inverters

This paper is a study of Multilevel Sinusoidal Pulse Width Modulation (MSPWM) methods; Phase Disposition (PD), Alternate Phase Opposition Disposition (APOD), Phase Opposition Disposition (POD) on a single phase Cascaded H-Bridge Multilevel inverter. Various factors such as amplitude modulation index (Ma), frequency modulation index (M-f), phase angle between carrier and reference modulating wave (phi) have been considered for simulation. Variation in these factors and their effect on inverter performance is evaluated. Factors such as DC bus utilization, output r.m.s voltage, total harmonic distortion (%THD), dominant harmonic order, switching losses are evaluated based on simulation results.