Enhancement of Strain Measurement Dynamic Range in Basic BOCDR System with Background Noise Reduction by Simple Filtering Calculation Scheme

2018 ◽  
Author(s):  
Ryu Shimizu ◽  
Masato Kishi ◽  
Kazuo Hotate
Keyword(s):  
Noise Reduction ◽  
Strain Measurement ◽  
Background Noise ◽  
Dynamic Range ◽  
Calculation Scheme

scholarly journals Automatic Modulation Classification Based on Deep Feature Fusion for High Noise Level and Large Dynamic Input

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 2117
Author(s):  
Hui Han ◽  
Zhiyuan Ren ◽  
Lin Li ◽  
Zhigang Zhu
Keyword(s):  
Neural Network ◽  
Frequency Domain ◽  
Noise Level ◽  
Background Noise ◽  
Dynamic Range ◽  
Feature Fusion ◽  
Superior Performance ◽  
Modulation Classification ◽  
High Background ◽  
Automatic Modulation Classification

Automatic modulation classification (AMC) is playing an increasingly important role in spectrum monitoring and cognitive radio. As communication and electronic technologies develop, the electromagnetic environment becomes increasingly complex. The high background noise level and large dynamic input have become the key problems for AMC. This paper proposes a feature fusion scheme based on deep learning, which attempts to fuse features from different domains of the input signal to obtain a more stable and efficient representation of the signal modulation types. We consider the complementarity among features that can be used to suppress the influence of the background noise interference and large dynamic range of the received (intercepted) signals. Specifically, the time-series signals are transformed into the frequency domain by Fast Fourier transform (FFT) and Welch power spectrum analysis, followed by the convolutional neural network (CNN) and stacked auto-encoder (SAE), respectively, for detailed and stable frequency-domain feature representations. Considering the complementary information in the time domain, the instantaneous amplitude (phase) statistics and higher-order cumulants (HOC) are extracted as the statistical features for fusion. Based on the fused features, a probabilistic neural network (PNN) is designed for automatic modulation classification. The simulation results demonstrate the superior performance of the proposed method. It is worth noting that the classification accuracy can reach 99.8% in the case when signal-to-noise ratio (SNR) is 0 dB.

Evaluation of a Transient Noise Reduction Strategy for Hearing Aids

2012 ◽  
Vol 23 (08) ◽  
pp. 606-615 ◽  
Author(s):  
HaiHong Liu ◽  
Hua Zhang ◽  
Ruth A. Bentler ◽  
Demin Han ◽  
Luo Zhang
Keyword(s):  
Noise Reduction ◽  
Hearing Aids ◽  
Background Noise ◽  
Hearing Aid ◽  
Sound Quality ◽  
T Test ◽  
Reduction Strategy ◽  
Speech Stimuli ◽  
Significant Difference ◽  
Speech Clarity

Background: Transient noise can be disruptive for people wearing hearing aids. Ideally, the transient noise should be detected and controlled by the signal processor without disrupting speech and other intended input signals. A technology for detecting and controlling transient noises in hearing aids was evaluated in this study. Purpose: The purpose of this study was to evaluate the effectiveness of a transient noise reduction strategy on various transient noises and to determine whether the strategy has a negative impact on sound quality of intended speech inputs. Research Design: This was a quasi-experimental study. The study involved 24 hearing aid users. Each participant was asked to rate the parameters of speech clarity, transient noise loudness, and overall impression for speech stimuli under the algorithm-on and algorithm-off conditions. During the evaluation, three types of stimuli were used: transient noises, speech, and background noises. The transient noises included “knife on a ceramic board,” “mug on a tabletop,” “office door slamming,” “car door slamming,” and “pen tapping on countertop.” The speech sentences used for the test were presented by a male speaker in Mandarin. The background noises included “party noise” and “traffic noise.” All of these sounds were combined into five listening situations: (1) speech only, (2) transient noise only, (3) speech and transient noise, (4) background noise and transient noise, and (5) speech and background noise and transient noise. Results: There was no significant difference on the ratings of speech clarity between the algorithm-on and algorithm-off (t-test, p = 0.103). Further analysis revealed that speech clarity was significant better at 70 dB SLP than 55 dB SPL (p < 0.001). For transient noise loudness: under the algorithm-off condition, the percentages of subjects rating the transient noise to be somewhat soft, appropriate, somewhat loud, and too loud were 0.2, 47.1, 29.6, and 23.1%, respectively. The corresponding percentages under the algorithm-on were 3.0, 72.6, 22.9, and 1.4%, respectively. A significant difference on the ratings of the transient noise loudness was found between the algorithm-on and algorithm-off (t-test, p < 0.001). For overall impression for speech stimuli: under the algorithm-off condition, the percentage of subjects rating the algorithm to be not helpful at all, somewhat helpful, helpful, and very helpful for speech stimuli were 36.5, 20.8, 33.9, and 8.9%, respectively. Under the algorithm-on condition, the corresponding percentages were 35.0, 19.3, 30.7, and 15.0%, respectively. Statistical analysis revealed there was a significant difference on the ratings of overall impression on speech stimuli. The ratings under the algorithm-on condition were significantly more helpful for speech understanding than the ratings under algorithm-off (t-test, p < 0.001). Conclusions: The transient noise reduction strategy appropriately controlled the loudness for most of the transient noises and did not affect the sound quality, which could be beneficial to hearing aid wearers.

Static strain measurement with submicro strain resolution and large dynamic range using twin grating Fabry-Perot sensor

2001 ◽  
Author(s):  
Mikhail G. Shlyagin ◽  
Pieter L. Swart ◽  
Serguei V. Miridonov ◽  
Anatoli A. Chtcherbakov ◽  
Ileana Marquez Borbon ◽  
...  
Keyword(s):  
Strain Measurement ◽  
Dynamic Range ◽  
Large Dynamic Range ◽  
Static Strain ◽  
Fabry Perot

Noise Reduction Technique for Digital Image Based Full Field Strain Measurement

2012 ◽  
Author(s):  
Yoshitaka Wada ◽  
Tomonari Furukawa
Keyword(s):  
Noise Reduction ◽  
Digital Image ◽  
Strain Measurement ◽  
Low Noise ◽  
Reduction Technique ◽  
Distortion Correction ◽  
Image Correlation ◽  
Full Field ◽  
Deformation Problem ◽  
Noise Reduction Technique

In recent years several techniques of full-field measurement have been studied by digital image correlation method, moiré interference method and holographic interferometry method and so on. Image based method can be easily applied to large deformation problem and moving specimen at slow speed. Because digital camera capabilities, which are high resolution, low noise and faster data transfer speed, have been improved, very small strain measurement can be achieved by those improvements. The improvement will widen those applications, for example, moving object at high speed and less 0.1% strain measurement which is almost the same accuracy with a precise strain gauge. In order to apply the advanced application, noise reduction for a digital image and lens distortion correction for an optical system should be developed. In this paper we propose noise reduction technique using statistical camera model to be applied to any kinds of digital cameras.

scholarly journals Modeling and Analysis of a Direct Time-of-Flight Sensor Architecture for LiDAR Applications

Sensors ◽  
2019 ◽  
Vol 19 (24) ◽  
pp. 5464 ◽  
Author(s):  
Preethi Padmanabhan ◽  
Chao Zhang ◽  
Edoardo Charbon
Keyword(s):  
Background Noise ◽  
3D Imaging ◽  
Dynamic Range ◽  
Time Of Flight ◽  
Operating Conditions ◽  
Exposure Limits ◽  
Depth Sensing ◽  
Wide Dynamic Range ◽  
High Background ◽  
Time Gating

Direct time-of-flight (DTOF) is a prominent depth sensing method in light detection and ranging (LiDAR) applications. Single-photon avalanche diode (SPAD) arrays integrated in DTOF sensors have demonstrated excellent ranging and 3D imaging capabilities, making them promising candidates for LiDARs. However, high background noise due to solar exposure limits their performance and degrades the signal-to-background noise ratio (SBR). Noise-filtering techniques based on coincidence detection and time-gating have been implemented to mitigate this challenge but 3D imaging of a wide dynamic range scene is an ongoing issue. In this paper, we propose a coincidence-based DTOF sensor architecture to address the aforementioned challenges. The architecture is analyzed using a probabilistic model and simulation. A flash LiDAR setup is simulated with typical operating conditions of a wide angle field-of-view (FOV = 40 ° ) in a 50 klux ambient light assumption. Single-point ranging simulations are obtained for distances up to 150 m using the DTOF model. An activity-dependent coincidence is proposed as a way to improve imaging of wide dynamic range targets. An example scene with targets ranging between 8–60% reflectivity is used to simulate the proposed method. The model predicts that a single threshold cannot yield an accurate reconstruction and a higher (lower) reflective target requires a higher (lower) coincidence threshold. Further, a pixel-clustering scheme is introduced, capable of providing multiple simultaneous timing information as a means to enhance throughput and reduce timing uncertainty. Example scenes are reconstructed to distinguish up to 4 distinct target peaks simulated with a resolution of 500 ps. Alternatively, a time-gating mode is simulated where in the DTOF sensor performs target-selective ranging. Simulation results show reconstruction of a 10% reflective target at 20 m in the presence of a retro-reflective equivalent with a 60% reflectivity at 5 m within the same FOV.

scholarly journals Sentence Recognition in Noise and Perceived Benefit of Noise Reduction on the Receiver and Transmitter Sides of a BICROS Hearing Aid

2013 ◽  
Vol 24 (10) ◽  
pp. 980-991 ◽  
Author(s):  
Kristi Oeding ◽  
Michael Valente
Keyword(s):  
Noise Reduction ◽  
Hearing Aids ◽  
Repeated Measures ◽  
Background Noise ◽  
Signal To Noise Ratio ◽  
Hearing Aid ◽  
Directional Microphones ◽  
Sentence Recognition ◽  
Clinically Significant ◽  
The Impact

Background: In the past, bilateral contralateral routing of signals (BICROS) amplification incorporated omnidirectional microphones on the transmitter and receiver sides and some models utilized noise reduction (NR) on the receiver side. Little research has examined the performance of BICROS amplification in background noise. However, previous studies examining contralateral routing of signals (CROS) amplification have reported that the presence of background noise on the transmitter side negatively affected speech recognition. Recently, NR was introduced as a feature on the receiver and transmitter sides of BICROS amplification, which has the potential to decrease the impact of noise on the wanted speech signal by decreasing unwanted noise directed to the transmitter side. Purpose: The primary goal of this study was to examine differences in the reception threshold for sentences (RTS in dB) using the Hearing in Noise Test (HINT) in a diffuse listening environment between unaided and three aided BICROS conditions (no NR, mild NR, and maximum NR) in the Tandem 16 BICROS. A secondary goal was to examine real-world subjective impressions of the Tandem 16 BICROS compared to unaided. Research Design: A randomized block repeated measures single blind design was used to assess differences between no NR, mild NR, and maximum NR listening conditions. Study Sample: Twenty-one adult participants with asymmetric sensorineural hearing loss (ASNHL) and experience with BICROS amplification were recruited from Washington University in St. Louis School of Medicine. Data Collection and Analysis: Participants were fit with the National Acoustic Laboratories’ Nonlinear version 1 prescriptive target (NAL-NL1) with the Tandem 16 BICROS at the initial visit and then verified using real-ear insertion gain (REIG) measures. Participants acclimatized to the Tandem 16 BICROS for 4 wk before returning for final testing. Participants were tested utilizing HINT sentences examining differences in RTS between unaided and three aided listening conditions. Subjective benefit was determined via the Abbreviated Profile of Hearing Aid Benefit (APHAB) questionnaire between the Tandem 16 BICROS and unaided. A repeated measures analysis of variance (ANOVA) was utilized to analyze the results of the HINT and APHAB. Results: Results revealed no significant differences in the RTS between unaided, no NR, mild NR, and maximum NR. Subjective impressions using the APHAB revealed statistically and clinically significant benefit with the Tandem 16 BICROS compared to unaided for the Ease of Communication (EC), Background Noise (BN), and Reverberation (RV) subscales. Conclusions: The RTS was not significantly different between unaided, no NR, mild NR, and maximum NR. None of the three aided listening conditions were significantly different from unaided performance as has been reported for previous studies examining CROS hearing aids. Further, based on comments from participants and previous research studies with conventional hearing aids, manufacturers of BICROS amplification should consider incorporating directional microphones and independent volume controls on the receiver and transmitter sides to potentially provide further improvement in signal-to-noise ratio (SNR) for patients with ASNHL.

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