Noise Minimization Research Articles

Real-Time Implementation of Parallel Architecture Based Noise Minimization from Speech Signals on FPGA

In recent years, the real time hardware implementation of LMS based adaptive noise cancellation on FPGA is becoming popular. There are several works reported in this area in the literature. However, NLMS based implementation of adaptive noise cancellation on FPGA using Xilinx System Generator (XSG) is not reported. This paper explores the various forms of parallel architecture based on NLMS algorithm and its hardware implementation on FPGA using XSG for noise minimization from speech signals. In total, the direct form, binary tree direct form and transposed form of parallel architecture of normalized least mean square (NLMS), delayed normalized least mean square and retimed delayed normalized least mean square algorithms are implemented on FPGA using hardware co-simulation model. The performance parameters (SNR and MSE) of these algorithms are analyzed for the adaptive noise cancellation system and the comparison is made with parallel architectures of least mean square (LMS), delayed least mean square, and retimed delayed least mean square algorithms respectively. The hardware utilization of all the said algorithms are also analyzed and compared. The result shows that NLMS based implementations outperform than that of LMS for all forms of parallel architecture for the given parameters with negligence increase in device utility. The binary tree direct form of retimed delayed NLMS achieves the maximum SNR improvement (39.83 dB) in comparison to other NLMS variants at the cost of optimum resource utilization.

2126 Optimizing a technique for visualizing retinal and choroidal blood flow noninvasively

OBJECTIVES/SPECIFIC AIMS: Diabetic retinopathy is an increasingly prevalent disease, difficult to screen for across the globe. We have developed and began optimizing an innovative technique to visualize and quantify retinal blood flow, to elucidate the role of the choroid in retinal pathologies such as diabetic retinopathy or choroidopathy. METHODS/STUDY POPULATION: Preliminary retinal was obtained from a surgical retina video library (Truvision, Goleta, CA, USA). Videos of different organs were recorded while vessels were occluded via a blood pressure cuff, using consumer-grade digital video cameras (NEX-5T, a7sii; Sony, New York, NY, USA). All other retinal videos were taken using a fundus camera (50×; Topcon, Oxland, NJ, USA) modified to support the above digital video cameras. All videos were processed using experimental software (MATLAB, Mathworks, Natick, MA, USA). RESULTS/ANTICIPATED RESULTS: Video imaging of the retina was optimized for lighting conditions and software requirements. Parameters were defined for the software imaging pipeline, such as frequency range of interest, sampling rate, and noise minimization. Software was developed to stabilize frames, accounting for eye saccades. Use of a biosensor enabled accurate measurement of pulse waveform, increasing signal-to-noise ratio. The optimal light requirements were determined such that adequate exposure of the retina is reproducible yet still comfortable for use in human subjects. DISCUSSION/SIGNIFICANCE OF IMPACT: This novel technique allows for an inexpensive, noninvasive, and reproducible ocular blood flow imaging platform. By optimizing this technique, we can proceed with our future plans for a pilot study to compare our imaging technique with the current standard, paving the way for future clinical studies.

Improving the quality of XAFS data.

Following the Q2XAFS Workshop and Satellite to IUCr Congress 2017 on `Data Acquisition, Treatment, Storage - quality assurance in XAFS spectroscopy', a summary is given of the discussion on different aspects of a XAFS experiment that affect data quality. Some pertinent problems ranging from sources and minimization of noise to harmonic contamination and uncompensated monochromator glitches were addressed. Also, an overview is given of the major limitations and pitfalls of a selection of related methods, such as photon-out spectroscopies and energy-dispersive XAFS, and of increasingly common applications, namely studies at high pressure, and time-resolved investigations of catalysts in operando. Advice on how to avoid or deal with these problems and a few good practice recommendations are reported, including how to correctly report results.

Crosstalk noise minimization in novel through silicon via structures

In recent trends, through silicon via (TSV) is essential Technologies for 3-D IC integration because of its short interconnects length and high interconnect density. Beyond the existing structure of TSV, this paper provides a novel structure to investigate the crosstalk effect and same is simulated by using a SPICE simulator and 3-D field solver. The structure of the TSV comprises of copper surrounding by insulating liner, and silicon substrate. In existing structures, silicon dioxide (Sio2) is used as insulating liner because of its material compatibility with silicon substrate. Several researches provide the problem of using Sio2 is due to its high dielectric constant; as a consequence delay will increase. Therefore, Sio2 is not appropriate for high performance applications. In this work, a novel TSV structure is reported to improve the TSV performance which uses poly-propylene polymer liner instead of oxide liner. Signal TSV is enclosed by using a poly-propylene liner and amid the analysis with doping region is created around the ground TSV. For comparison purposes, conventional and proposed TSV structures are simulated. The proposed TSV’s structure simulation results in 30% decrease in crosstalk over existing TSV structures.

A new approach for an FE-model optimization of a MEMS piezoelectric accelerometer for implantable hearing devices

Totally implantable hearing devices have been proposed as a solution to mitigate the constraints related to the presence of external elements in traditional hearing devices. This work reports on a novel approach for the development of a MEMS piezoelectric accelerometer as an implantable sensor for hearing devices. Traditionally these sensors are designed for maximum sensitivity; however, the primary bottleneck for this type of transducer is the internal noise level. Two differential evolution optimization routines were developed. The first used sensitivity maximization whereas the second seeks minimization of the equivalent input noise (EIN). Both methods were applied to different designs of Lead Zirconate Titanate (PZT) MEMS piezoelectric accelerometer in the frequency range of 250 Hz to 8 kHz with layer thickness varying from 0.1 μm to 1 μm. In the latter approach, the sensor's acceleration noise was estimated analytically, considering capacitance and charge response acquired through finite element mode...

Aspects regarding manufacturing technologies of composite materials for brake pad application

Current needs in road safety, requires the development of new technical solutions for automotive braking system. Their safe operation is subject to following factors: concept design, materials used and electronic control. Among the factors previously listed, choice of materials and manufacturing processes are difficult stage but very important for achieving technical performance and getting a relatively small cost of constituting parts of brake system. The choice is based on the promotion of organic composite material, popular in areas where the weight of materials plays an important role. The brake system is composed of many different parts including brake pads, a master cylinder, wheel cylinders and a hydraulic control system. The brake pads are an important component in the braking system of automotive. These are of different types, suitable for different types of automotive and engines. Brake pads are designed for friction stability, durability, minimization of noise and vibration. The typology of the brake pads depends on the material which they are made. The aim of this paper is to presents the manufacturing technologies for ten recipes of composite material used in brake pads applications. In this work will be done: choosing the constituents of the recipes, investigation of their basic characteristics, setting the proportions of components, obtaining the composite materials in laboratory, establishing the parameters of manufacturing technology and technological analysis.

Instrumentation for low noise nanopore-based ionic current recording under laser illumination.

We describe a nanopore-based optofluidic instrument capable of performing low-noise ionic current recordings of individual biomolecules under laser illumination. In such systems, simultaneous optical measurements generally introduce significant parasitic noise in the electrical signal, which can severely reduce the instrument sensitivity, critically hindering the monitoring of single-molecule events in the ionic current traces. Here, we present design rules and describe simple adjustments to the experimental setup to mitigate the different noise sources encountered when integrating optical components to an electrical nanopore system. In particular, we address the contributions to the electrical noise spectra from illuminating the nanopore during ionic current recording and mitigate those effects through control of the illumination source and the use of a PDMS layer on the SiNx membrane. We demonstrate the effectiveness of our noise minimization strategies by showing the detection of DNA translocation events during membrane illumination with a signal-to-noise ratio of ∼10 at 10 kHz bandwidth. The instrumental guidelines for noise minimization that we report are applicable to a wide range of nanopore-based optofluidic systems and offer the possibility of enhancing the quality of synchronous optical and electrical signals obtained during single-molecule nanopore-based analysis.

Gain stabilization and noise minimization for SiPMs at cryogenic temperatures

The performance of solid-state photon detectors such as avalanche photodiodes or silicon photomultipliers (SiPMs) is strongly affected by temperature. Important device characteristics for the detection of low light levels or single photons are photon detection efficiency, dark noise, and gain. In the present work the C-series SiPMs from SensL was characterized in cryogenic environments. At 77 K the SiPMs proved to be an excellent choice for single photon detection and an operation point with minimum noise contributions was found. At 4 K the performance was degraded, exhibiting a smaller gain and a larger noise.

An Approach to Minimization of Drive Train Noise Through Redesign of Engine Mounts

Drive train noise is more annoying for passenger. For a V-hull base mine protected 4WD defence-vehicle, metallic noise was observed from drive train. To resolve this kind of NVH problem of complicated vehicle like defence required commending knowledge base and experience or say know-how. The critical constraint of subject vehicle was fixed position of engine or engine mounts and transfer case. This causes higher slope equivalent angle of first drive shaft with respect to the installation standard. Noise issue observed as consequence of aforesaid issue which has impact installation parameters of torsional, inertia and secondary coupling excitation frequencies. In this context, a structured methodology has been followed in present work for finding root causes and optimizing the design to come out with optimum solution. Engine mounts have major influence to finalize first drive line slope angle. Hence, re-designing and verification have been done for engine mounts considering its major design parameters and criteria (e.g. shape factors, shore hardness, static deflection and isolation efficiency). At the same time, effects of those changes have been verified theoretically and practically on vehicle. Pass by noise, cabin inside noise, isolation efficiency of front and rear mounts and vehicle floor vibration level were measured. The objective of the exercise is to find out a solution for minimization of drive-train noise.

Optimizing source placement for noise minimization using hybrid acoustic simulation

Environmental noises can have a large impact on workplace productivity and health. We address the problem of designing large CAD structures that automatically meet the noise guidelines and standards. We present a novel approach that determines the optimal placement of sound sources such as generators, machinery, fans and HVAC appliances that can conform to these design requirements in indoor scenes. Our approach uses a hybrid sound propagation algorithm that combines elements of both geometric and wave-based techniques for handling higher and lower frequencies, respectively. We use an efficient simulated annealing approach for acoustic optimization that uses impulse response caching and sound source clustering to improve the convergence time. Finally, we present our approach in the context of a traditional CAD pipeline, where noise conformance requirements can be integrated during the early stages of the digital design phase. We highlight the approach’s performance on many complex CAD models corresponding to an office and a warehouse.

Speech enhancement using Teager energy operated ERB-like perceptual wavelet packet decomposition

In recent past, wavelet packet (WP) based speech enhancement techniques have been gaining popularity due to their inherent nature of noise minimization. WP based techniques appeared as more robust and efficient than short-time Fourier transform based methods. In the present work, a speech enhancement method using Teager energy operated equal rectangular bandwidth (ERB)-like WP decomposition has been proposed. Twenty four sub-band perceptual wavelet packet decomposition (PWPD) structure is implemented according to the auditory ERB scale. ERB scale based decomposition structure is used because the central frequency of the ERB scale distribution is similar to the frequency response of the human cochlea. Teager energy operator is applied to estimate the threshold value for the PWPD coefficients. Lastly, Wiener filtering is applied to remove the low frequency noise before final reconstruction stage. The proposed method has been applied to evaluate the Hindi sentences database, corrupted with six noise conditions. The proposed method’s performance is analysed with respect to several speech quality parameters and output signal to noise ratio levels. Performance indicates that the proposed technique outperforms some traditional speech enhancement algorithms at all SNR levels.

Graph Laplacian Regularization With Procrustes Analysis for Sensor Node Localization

In this paper, we investigate the problem of sensor node localization and propose a non-linear semi supervised noise minimization algorithm through iterative manifold learning. The method works on the observation that noisy data lie on a higher dimension space even though the actual data are embedded in a low dimensional manifold. The collective labeled and unlabeled data are represented as a weighted graph. A prediction function is created based on the available labeled data along with manifold learning to exploit the intrinsic geometry. On top of prediction function, iterative feedback mechanism is used, which incrementally flattens the higher dimensional manifold. This reduces the error boundary in each stage for every data point. Result found to converge after a few iterations. This is followed by localized Procrustes analysis to further reduce the error. Experiment using TelosB motes and simulation with labeled and unlabeled data show that the proposed technique is able to reduce the noise, on an average, by around 70%. Results also show that the mechanism is able to localize the sensor nodes with high accuracy and outperforms the baseline method and LapRLS in different conditions.

Multi-objective optimization for gene expression noise reduction in a synthetic gene circuit

Stochasticity in biological systems often referred to as gene expression noise is ubiquitous. The main sources of this noise come about in two ways. The implicit randomness of the biochemical reactions generates intrinsic noise inside the cell. Other cellular processes are themselves products that vary over time and from each cell to another, producing the so-called extrinsic noise. Controlling the mean expression level of a gene while reducing its noise is a challenge in many applications of Synthetic Biology. In previous works, we proposed a gene synthetic circuit to reduce gene expression noise while achieving a desired mean expression level. The circuit combines a negative feedback loop and a cell-to-cell communication mechanism based on quorum sensing. In this work, we use a multi-objective optimization design approach to find the best values for the tunable-in-the-lab parameters that, for a given desired mean expression value, achieve minimization of gene expression noise caused by intrinsic and extrinsic fluctuations. Our approach allows tuning the circuit parameters required to minimize noise effects, providing results which prove in accordance with genome-wide experimental data reported in the literature. Exploring different scenarios, either considering only intrinsic noise or considering both extrinsic and intrinsic ones, we find that the design strategies obtained for both cases are not transferable. Thus, designing the circuit parameters taking into account only intrinsic noise yields a sub-optimal design with decreased performance when evaluated in a scenario where both extrinsic and intrinsic noise are present.

Integrated, Multichannel Readout Circuit Based on Chopper Amplifier Concept for FET-Based THz Detectors

This work presents the integrated, multichannel readout circuit dedicated to FET-based THz detectors. Described solution provides an unique approach to FET detectors readout, able to replace the measurement equipment deploying the lock-in technique and to eliminate the necessity of modulating the THz wave. The IC proposed by the authors is based on the chopper amplifier architecture, enhanced and adapted for multichannel signal processing. It also ensures significant 1/f noise minimisation, which is the key requirement for the FET-based detectors readout. The circuit prototypes were manufactured in standard 350 nm CMOS process (AMS A.G.) and then measured in the dedicated test set-up.

Comparison of lithological mapping results from airborne hyperspectral VNIR-SWIR, LWIR and combined data

This study investigates using the Airborne Hyperspectral Imaging Systems (AISA) visible and short-wave infrared (SWIR) and Spatially Enhanced Broadband Array Spectrograph System (SEBASS) longwave infrared (LWIR) (2 and 4m spatial resolution, respectively) imagery independently and in combination to produce detailed lithologic maps in a subarctic region (Cape Smith Belt, Nunavik, Canada) where regionally metamorphosed lower greenschist mafic, ultramafic and sedimentary rocks are exposed in the presence of lichen coatings. We make use of continuous wavelet analysis (CWA) to improve the radiometric quality of the imagery through the minimization of random noise and the enhancement of spectral features, the minimization of residual errors in the ISAC radiometric correction and target temperature estimation in the case of the LWIR data, the minimization of line to line residual calibration effects that lead to inconsistencies in data mosaics, and the reduction in variability of the spectral continuum introduced by variable illumination and topography. The use of CWA also provides a platform to directly combine the wavelet scale spectral profiles of the SWIR and LWIR after applying a scalar correction factor to the LWIR such that the dynamic range of two data sets have equal weight. This is possible using CWA as the datasets are normalized to a zero mean allowing spectra from different spectral regions to be adjoined.Lithologic maps are generated using an iterative spectral unmixing approach with image spectral endmembers extracted from the SWIR and LWIR imagery based on locations defined from previous work of the study area and field mapping information. Unmixing results of the independent SWIR and LWIR data, and the combined data show clear benefits to using the CWA combined imagery. The analysis showed SWIR and LWIR imagery highlight similar regions and spatial distributions for the three ultramafic units (dunite, peridotite, pyroxenite). However, significant differences are observed for quartz-rich sediments, with the SWIR overestimating the distribution of these rocks whereas the LWIR provided more consistent results compared with existing maps. Both SWIR and LWIR imagery were impacted by the pervasive lichen coatings on the mafic rocks (basalts and gabbros), although the SWIR provided better results than the LWIR. Limitations observed for the independent data sets were removed using the combined spectral data resulting in all geologically meaningful units mapped correctly in comparison with existing geological maps.

Promoter shape varies across populations and affects promoter evolution and expression noise.

Animal promoters initiate transcription either at precise positions (narrow promoters) or dispersed regions (broad promoters), a distinction referred to as promoter shape. Although highly conserved, the functional properties of promoters with different shapes and the genetic basis of their evolution remain unclear. Here we used natural genetic variation across a panel of 81 Drosophila lines to measure changes in transcriptional start site (TSS) usage, identifying thousands of genetic variants affecting transcript levels (strength) or the distribution of TSSs within a promoter (shape). Our results identify promoter shape as a molecular trait that can evolve independently of promoter strength. Broad promoters typically harbor shape-associated variants, with signatures of adaptive selection. Single-cell measurements demonstrate that variants modulating promoter shape often increase expression noise, whereas heteroallelic interactions with other promoter variants alleviate these effects. These results uncover new functional properties of natural promoters and suggest the minimization of expression noise as an important factor in promoter evolution.

Performance Comparison of Different Affine Projection Algorithms for Noise Minimization from Speech Signals

Performance Comparison of Different Affine Projection Algorithms for Noise Minimization from Speech Signals

Speech enhancement using voiced speech probability based wavelet decomposition

Wavelet-based speech enhancement technique has gained popularity for its inherent nature of noise minimization. Utilizing this advantage, in this work, a new approach is taken to design a speech enhancement system by using Voiced Speech Probability (VSP) based Wavelet Decomposition (WD). The VSP-based improved Voice Activity Detector (VAD) is designed to separate voiced/unvoiced frames on the basis of the probability calculated by the likelihood ratio of two Gaussian Mixture Models (GMMs). A gain estimator is integrated with the WD stage to minimize the Mean Square Error (MSE). This proposed method has been evaluated on a subset of TIMIT database corrupted with five different noise conditions such as machine gun noise, white noise, pink noise, f16 noise, and operations room noise at four Signal to Noise Ratio (SNR) levels. This method is also compared with traditional algorithms, and significant performance improvement is observed.

A Multicriteria Analysis for the Green VRP: A Case Discussion for the Distribution Problem of a Spanish Retailer

Abstract: This research presents the group of green vehicle routing problems with environmental costs translated into money versus production of noise, pollution and fuel consumption. This research is focused on multi-objective green logistics optimization. Optimality criteria are environmental costs: minimization of amount of money paid as externality cost for noise, pollution and costs of fuel versus minimization of noise, pollution and fuel consumption themselves. Some mixed integer programming formulations of multi-criteria vehicle routing problems have been considered. Mathematical models were formulated under assumption of existence of asymmetric distance-based costs and use of homogeneous fleet. The exact solution methods are applied for finding optimal solutions. The software used to solve these models is the CPLEX solver with AMPL programming language. The researchers were able to use real data from a Spanish company of groceries. Problems deal with green logistics for routes crossing the Spanish regions of Navarre, Basque Country and La Rioja. Analyses of obtained results could help logistics managers to lead the initiative in area of green logistics by saving money paid for environmental costs as well as direct cost of fuel and minimization of pollution and noise.

Optimization of contrast-enhanced breast imaging: Analysis using a cascaded linear system model.

Contrast-enhanced (CE) breast imaging involves the injection contrast agents (i.e., iodine) to increase conspicuity of malignant lesions. CE imaging may be used in conjunction with digital mammography (DM) or digital breast tomosynthesis (DBT) and has shown promise in improving diagnostic specificity. Both CE-DM and CE-DBT techniques require optimization as clinical diagnostic tools. Physical factors including x-ray spectra, subtraction technique, and the signal from iodine contrast, must be considered to provide the greatest object detectability and image quality. We developed a cascaded linear system model (CLSM) for the optimization of CE-DM and CE-DBT employing dual energy (DE) subtraction or temporal (TE) subtraction. We have previously developed a CLSM for DBT implemented with an a-Se flat panel imager (FPI) and filtered backprojection (FBP) reconstruction algorithm. The model is used to track image quality metrics - modulation transfer function (MTF) and noise power spectrum (NPS) - at each stage of the imaging chain. In this study, the CLSM is extended for CE breast imaging. The effect of x-ray spectrum (varied by changing tube potential and the filter) and DE and TE subtraction techniques on breast structural noise was measured was studied and included as a deterministic source of noise in the CLSM. From the two-dimensional (2D) and three-dimensional (3D) MTF and NPS, the ideal observer signal-to-noise ratio (SNR), also known as the detectability index (d'), may be calculated. Using d' as a FOM, we discuss the optimization of CE imaging for the task of iodinated contrast object detection within structured backgrounds. Increasing x-ray energy was determined to decrease the magnitude of structural noise and not its correlation. By performing DE subtraction, the magnitude of the structural noise was further reduced at the expense of increased stochastic (quantum and electronic) noise. TE subtraction exhibited essentially no residual structural noise at the expense of increased quantum noise, even over that of the DE case. For DE subtraction, optimization of dose weighting to the HE view (fh ) results in the minimization of quantum noise. Both subtraction weighting factor (wSub ) and the iodine contrast signal were dependent on the LE and HE x-ray spectra. To best detect a 5 mm Gaussian lesion with 5 mg/ml of iodine within a 4 cm thick breast, it was found that the high energy (HE) view should be acquired with a tube potential of 47 kVp (W/Ti spectrum) and the low energy (LE) view with a potential of 23 kVp (W/Rh spectrum). Due to the complete removal of structural noise, TE subtraction produced much higher d' than DE subtraction both as a function of mean glandular dose and iodine concentration. We have shown the effect of increasing x-ray energy as well as projection domain subtraction on breast structural noise. Further, we have exhibited the utility of the CLSM for DE and TE subtraction CE imaging in the optimization of imaging parameters such as x-ray energy, fh , and wSub as well as guiding the understanding of their effects on image contrast and noise.