Frequency Spectral Information Research Articles

Development of a Compact, Cost-Effective Photoacoustic Spectral Response Measurement System for Biomedical Applications

Photoacoustic spectral response (PASR) technique is a pump-probe technique that provides acoustic spectral information of any biological tissue. This extracted information acts as a signature of the biological tissue. The experimental setups can be bulky, expensive, and involve complex operation due to the requirement of costly Q-switched lasers, complex optics, and limited wavelength. On the other side, setup requires high-frequency signal conditioning, a high-speed oscilloscope, and a computing device to process, analyze, and monitor the acquired signal. This paper presents a compact, cost-effective measurement instrument to measure and display the time-domain and frequency spectral information for biomedical applications. The developed electronic hardware is used to perform real-time signal conditioning; subsequently, conditioned photoacoustic (PA) data were acquired with a speed of 30 MSPS, and the results were sent to a monitor to display. Developed hardware contains a high-frequency pre-amplifier, low-pass filter, electrically isolated trigger circuit, and a 12-bit high-speed analog-to-digital converter to generate digital data, which is further analyzed by a high-speed microcontroller. After calibration of the proposed experimental setup, the developed PA tool is applied to distinguishing lung and liver tissues, and the statistical results corroborate the consistency of the proposed PA-based data acquisition system.

Save Muscle Information-Unfiltered EEG Signal Helps Distinguish Sleep Stages.

Based on the well-established biopotential theory, we hypothesize that the high frequency spectral information, like that higher than 100Hz, of the EEG signal recorded in the off-the-shelf EEG sensor contains muscle tone information. We show that an existing automatic sleep stage annotation algorithm can be improved by taking this information into account. This result suggests that if possible, we should sample the EEG signal with a high sampling rate, and preserve as much spectral information as possible.

Dual-layer optimized selective information fusion using multi-source multi-component mechanical signals for mill load parameters forecasting

Abstract Ball mill is a heavy mechanical device necessary for grinding. Mill load parameters (MLP) relate to production economic indices and process safety. Mechanical signals of the ball mill are used to estimate MLP by domain experts. However, they can only estimate familiar mills effectively in certain time because of human limitation. A new dual-layer optimized selective information fusion is proposed based on the analysis of the characteristics of mill mechanical signals and cognitive behavior of the domain expert for MLP forecasting (MLPF). An ensemble construction strategy based on multi-component mechanical signals adaptive decomposition is employed to build candidate sub-models by using kernel partial least squares (KPLS). The dual-layer optimization strategy is proposed to build selective ensemble (SEN) KPLS (SENKPLS) with optimized ensemble sub-models and their coefficients, thus realizing the trade-off between prediction accuracies and diversity implicitly. The MLPF models based on SENKPLS are constructed by selective fusion multi-source multi-scale frequency spectral information in terms of the auditory perception process of the simulation domain experts. Results show that the proposed strategy can obtain better forecasting results than other state-of-the-art methods.

Image-Guided Nanopositioning Scheme for SEM

Positioning of micro-nanoobjects inside a scanning electron microscope (SEM) for manipulation is a key and challenging task to perform. Often it is performed by skilled operators via teleoperation, which is tedious and lacks repeatability. In this paper, rendering this task as an image-guided problem, we present a frequency domain scheme for automatic control of positioning platform movements. The designed controller uses the relative global image motion computed using the frequency spectral information of the images as visual signal and can provide control up to five degrees of freedom. The proposed approach is validated in simulations as well as experimentally using a high-resolution piezo-positioning platform mounted inside a SEM vacuum chamber. The obtained results quantify the performance of the proposed nanopositioning scheme.

Damage-sensitive features from non-linear vibration response of reinforced concrete structures

Reinforced concrete structures respond in non-linear manner under dynamic loads even at low levels of vibration. This causes softening in concrete which may result in the unstable vibration. By considering the non-linearity, the effects of amplitude of vibration on the modal characteristics can be used to extract damage-sensitive features. In this article, investigations carried out on the phenomena associated with non-linear vibration, which were observed during the vibration tests on damaged reinforced concrete structures, are discussed. For effectively identifying the non-linear damage features in reinforced concrete structures from the frequency spectral information, an appropriate vibration testing procedure is formulated in this study. Damage features are evaluated from the changes in vibration amplitude with frequency at different damage levels under various types of excitations and their force levels. Damage indicators based on basic signal statistics and non-linearity in vibration responses are evaluated. Using the phase-plane information obtained from various damage scenarios, non-linear damage indices have been formulated. Another significant non-linear damage feature has been identified by the occurrence of higher harmonics observed by analysing the spectral density functions obtained from the frequency domain decomposition. The results obtained from this study would pave the way for identifying the damage in heterogeneous and non-linear structures such as reinforced concrete.

Speech Recognition Using HMM with MFCC-An Analysis Using Frequency Specral Decomposion Technique

This paper presents an approach to the recognition of speech signal using frequency spectral information with Mel frequency for the improvement of speech feature representation in a HMM based recognition approach. A frequency spectral information is incorporated to the conventional Mel spectrum base speech recognition approach. The Mel frequency approach exploits the frequency observation for speech signal in a given resolution which results in resolution feature overlapping resulting in recognition limit. Resolution decomposition with separating frequency is mapping approach for a HMM based speech recognition system. The Simulation results show an improvement in the quality metrics of speech recognition with respect to computational time, learning accuracy for a speech recognition system.

The use of fundamental frequency information by cochlear implant patients with residual low‐frequency hearing

Recent studies have demonstrated significant benefits of complementing the electric hearing provided by a cochlear implant (CI) with residual low‐frequency acoustic hearing. It has been suggested that the benefit of low‐frequency hearing (<250 Hz) is due to improved representation of fundamental frequency (F0). It was hypothesized that removing F0 information would negatively impact speech perception in bimodal CI patients (EAS) more so when they are using both modes of perception. It was further hypothesized that these patients' more effective use of F0 information would result in higher intelligibility scores and less unpredicted lexical boundary errors (LBEs) in a speech transcription task. Six EAS patients transcribed normal and F0‐flattened phrases. Results indicate EAS patients demonstrated a significant benefit from the residual low‐frequency acoustic hearing and perform better in this mode. Five of the six EAS patients were able to transcribe the normal phrases with greater accuracy than the flat F0 phrases in both conditions. These patients correctly parsed lexical boundaries and transcribed phonemic targets with greater accuracy in the bimodal condition. These results demonstrate the importance of pitch and low frequency spectral information in the perception of speech.

Edge density fluctuation characterization in H -mode and polarimetry measurement via the FIReTIP system on NSTX

The edge interferometry channel of the far infrared tangential interferometer polarimeter (FIReTIP) is used to characterize the localized edge density fluctuations during the L/H transition in conjunction with other edge diagnostic systems on the National Spherical Tokamak Experiment (NSTX). With the high IF frequency employing a “Stark-tuned” laser as local oscillator, it is possible to measure the absolute level of fluctuations at high time resolution. Density fluctuation measurements using FIReTIP are feasible at both the high field side and the low field side boundary throughout the plasma shot. The normalized level of measured density fluctuations was in the range of 0.01–0.3 depending upon the channel location and the plasma confinement. The experimental results showed that the sampling rate of 500 KHz was sufficiently high to produce valuable frequency spectral information during the L/H transition, ELMs period and TAE/f.b.s activities. The improved polarimetry measurement was introduced for the para/diamagnetic study of the NSTX plasma. Multichannel operation of FIReTIP with high resolution density measurement provides promising opportunities as a density fluctuation diagnostic system for turbulence/transport and boundary physics studies as well as the robust density measurement for plasma operation. In this article, a brief description of the upgraded portion of the FIReTIP system will be given together with the experimental results of spectral analysis of the edge fluctuations and assessments on polarimetry signals.

The determination of the spectral turnover in faint Compact Steep-Spectrum radio sources using the VLA at 74 MHz

We carried out VLA observations in A configuration at 74 MHz of a new sample of faint Compact Steep-Spectrum (CSS) radio sources as part of a comprehensive project to study the nature and evolution of peaked-spectrum radio sources. In conjunction with higher frequency spectral information this has enabled us to determine the peak frequency and peak flux density of the spectral turnover for 35 faint CSS radio sources. Spectra are presented. An analysis is given of the quality of the images and their suitability for integrated intensity measurements of the CSS radio sources.

Segmentation of SAR images using the wavelet transform

Multiresolution representation of images using the wavelet transform is a new approach for the analysis of image information content. The transform can be computed efficiently by a pyramidal algorithm based on convolution with quadrature mirror filters. The result is a set of subband images which consists of a lower resolution version of the original image and a sequence of detail images containing higher frequency spectral information. We used this representation for the supervised segmentation of polarimetric SAR images of the San Francisco Bay area acquired by the airborne JPL system for identifying various terrain covers. Since the wavelet transform generates the localized spatial and spectral information simultaneously, detailed knowledge of the texture variations within an image can be extracted from the data in the spectral subbands. The segmentation algorithm developed in this paper is formulated by taking into consideration both the intensity and the texture information. For polarimetric SAR images, the classification accuracy can be enhanced, if the combined data from copolarized and cross-polarized images are used in the discrimination process. In contrast to other texture segmentation approaches, this algorithm does not require extensive calculations.©1993 John Wiley & Sons Inc