IF Estimation for Multicomponent Signals Using Image Processing Techniques in the Time-Frequency Domain

This paper presents a method for estimating the instantaneous frequency (IF) of multicomponent signals. The technique involves, firstly, the transformation of the one dimensional signal to the two dimensional time-frequency domain using a reduced interference quadratic time-frequency distribution. IF estimation of signal components is then achieved by implementing two image processing steps: local peak detection of the time--frequency (TF) representation followed by an image processing technique called component linking. The proposed IF estimator is tested on noisy synthetic monocomponent and multicomponent signals exhibiting linear and nonlinear laws. For low signal to noise ratio (SNR) environments, a time-frequency peak filtering preprocessing step is used for signal enhancement. Application of the IF estimation scheme to real signals is illustrated with newborn EEG signals. Finally, to illustrate the potential use of the proposed IF estimation method in classifying signals based on their TF components' IFs, a classification method using least squares data-fitting is proposed and illustrated on synthetic and real signals

EMD-based filtering (EMDF) of low-frequency noise for speech enhancement

An Empirical Mode Decomposition based filtering (EMDF) approach is presented as a post-processing stage for speech enhancement. This method is particularly effective in low frequency noise environments. Unlike previous EMD based denoising methods, this approach does not make the assumption that the contaminating noise signal is fractional Gaussian Noise. An adaptive method is developed to select the IMF index for separating the noise components from the speech based on the second-order IMF statistics. The low frequency noise components are then separated by a partial reconstruction from the IMFs. It is shown that the proposed EMDF technique is able to suppress residual noise from speech signals that were enhanced by the conventional optimallymodified log-spectral amplitude approach which uses a minimum statistics based noise estimate. A comparative performance study is included that demonstrates the effectiveness of the EMDF system in various noise environments, such as car interior noise, military vehicle noise and babble noise. In particular, improvements up to 10 dB are obtained in car noise environments. Listening tests were performed that confirm the results

Real-time extraction of growth rates from rotating substrates during molecular-beam epitaxy

We present a method for measuring molecular‐beam epitaxy growth rates in near real‐time on rotating substrates. This is done by digitizing a video image of the reflection high‐energy electron diffraction screen, automatically tracking and measuring the specular spot width, and using numerical techniques to filter the resulting signal. The digitization and image and signal processing take approximately 0.4 s to accomplish, so this technique offers the molecular‐beam epitaxy grower the ability to actively adjust growth times in order to deposit a desired layer thickness. The measurement has a demonstrated precision of approximately 2%, which is sufficient to allow active control of epilayer thickness by counting monolayers as they are deposited. When postgrowth techniques, such as frequency domain analysis, are also used, the reflection high‐energy electron diffraction measurement of layer thickness on rotating substrates improves to a precision of better than 1%. Since all of the components in the system described are commercially available, duplication is straightforward

Enhanced monopulse radar tracking using fractional Fourier filtering in the presence of interference

Monopulse radars are used to track a target that appears in the look direction beam width. Significant distortion is produced when manmade high power interference (jamming) is introduced to the radar processor through the radar antenna main lobe (main lobe interference) or antenna side lobe (side lobe interference). This leads to errors in the target tracking angles that may cause target mistracking. A new monopulse radar structure is presented in this paper which addresses this problem. This structure is based on the use of optimal Fractional Fourier Transform (FrFT) filtering. The improved performance of the new monopulse radar structure over the traditional monopulse processor is assessed using standard deviation angle estimation error (STDAE) for a range of simulated environments. The proposed system configurations with the optimum FrFT filters is shown to reduce the interfered signal and to minimize the STDAE for monopulse processors

Moving Difference (MDIFF) Non-adiabatic Rapid Sweep (NARS) EPR of Copper(II)

Non-adiabatic rapid sweep (NARS) EPR spectroscopy has been introduced for application to nitroxide-labeled biological samples (Kittell et al., 2011). Displays are pure absorption, and are built up by acquiring data in spectral segments that are concatenated. In this paper we extend the method to frozen solutions of copper-imidazole, a square planar copper complex with four in-plane nitrogen ligands. Pure absorption spectra are created from concatenation of 170 5-gauss segments spanning 850 G at 1.9 GHz. These spectra, however, are not directly useful since nitrogen superhyperfine couplings are barely visible. Application of the moving difference (MDIFF) algorithm to the digitized NARS pure absorption spectrum is used to produce spectra that are analogous to the first harmonic EPR. The signal intensity is about four times higher than when using conventional 100 kHz field modulation, depending on line shape. MDIFF not only filters the spectrum, but also the noise, resulting in further improvement of the SNR for the same signal acquisition time. The MDIFF amplitude can be optimized retrospectively, different spectral regions can be examined at different amplitudes, and an amplitude can be used that is substantially greater than the upper limit of the field modulation amplitude of a conventional EPR spectrometer, which improves the signal-to-noise ratio of broad lines

Systems and methods for physiological signal enhancement and biometric extraction using non-invasive optical sensors

A system and method for signal processing to remove unwanted noise components including: (i) wavelength-independent motion artifacts such as tissue, bone and skin effects, and (ii) wavelength-dependent motion artifact/noise components such as venous blood pulsation and movement due to various sources including muscle pump, respiratory pump and physical perturbation. Disclosed are methods, analytics, and their uses for reliable perfusion monitoring, arterial oxygen saturation monitoring, heart rate monitoring during daily activities and in hospital settings and for extraction of physiological parameters such as respiration information, hemodynamic parameters, venous capacity, and fluid responsiveness. The system and methods disclosed are extendable to include monitoring platforms for perfusion, hypoxia, arrhythmia detection, airway obstruction detection and sleep disorders including apnea.Board of Regents, University of Texas Syste

Single Molecule DNA Detection with an Atomic Vapor Notch Filter

The detection of single molecules has facilitated many advances in life- and material-sciences. Commonly, it founds on the fluorescence detection of single molecules, which are for example attached to the structures under study. For fluorescence microscopy and sensing the crucial parameters are the collection and detection efficiency, such that photons can be discriminated with low background from a labeled sample. Here we show a scheme for filtering the excitation light in the optical detection of single stranded labeled DNA molecules. We use the narrow-band filtering properties of a hot atomic vapor to filter the excitation light from the emitted fluorescence of a single emitter. The choice of atomic sodium allows for the use of fluorescent dyes, which are common in life-science. This scheme enables efficient photon detection, and a statistical analysis proves an enhancement of the optical signal of more than 15% in a confocal and in a wide-field configuration.Comment: 9 pages, 5 figure

Blind Curvelet based Denoising of Seismic Surveys in Coherent and Incoherent Noise Environments

The localized nature of curvelet functions, together with their frequency and dip characteristics, makes the curvelet transform an excellent choice for processing seismic data. In this work, a denoising method is proposed based on a combination of the curvelet transform and a whitening filter along with procedure for noise variance estimation. The whitening filter is added to get the best performance of the curvelet transform under coherent and incoherent correlated noise cases, and furthermore, it simplifies the noise estimation method and makes it easy to use the standard threshold methodology without digging into the curvelet domain. The proposed method is tested on pseudo-synthetic data by adding noise to real noise-less data set of the Netherlands offshore F3 block and on the field data set from east Texas, USA, containing ground roll noise. Our experimental results show that the proposed algorithm can achieve the best results under all types of noises (incoherent or uncorrelated or random, and coherent noise)