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At least 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
NASA NTRS1989

A programmable image compression system

A programmable image compression system which has the necessary flexibility to address diverse imaging needs is described. It can compress and expand single frame video images (monochrome or color) as well as documents and graphics (black and white or color) for archival or transmission applications. Through software control, the compression mode can be set for lossless or controlled quality coding; the image size and bit depth can be varied; and the image source and destination devices can be readily changed. Despite the large combination of image data types, image sources, and algorithms, the system provides a simple consistent interface to the programmer. This system (OPTIPAC) is based on the TITMS320C25 digital signal processing (DSP) chip and has been implemented as a co-processor board for an IBM PC-AT compatible computer. The underlying philosophy can readily be applied to different hardware platforms. By using multiple DSP chips or incorporating algorithm specific chips, the compression and expansion times can be significantly reduced to meet performance requirements.

Farrelle, Paul M.↗
DOE OSTI2022

Automatic Waveform Quality Control for Surface Waves Using Machine Learning

Surface-wave seismograms are widely used by researchers to study Earth’s interior and earthquakes. To extract information reliably and robustly from a suite of surface waveforms, the signals require quality control screening to reduce artifacts from signal complexity and noise. This process has usually been completed by human experts labeling each waveform visually, which is time consuming and tedious for large data sets. We explore automated approaches to improve the efficiency of waveform quality control processing by investigating logistic regression, support vector machines, K-nearest neighbors, random forests (RF), and artificial neural networks (ANN) algorithms. To speed up signal quality assessment, we trained these five machine learning (ML) methods using nearly 400,000 human-labeled waveforms. The ANN and RF models outperformed other algorithms and achieved a test accuracy of 92%. We evaluated these two best-performing models using seismic events from geographic regions not used for training. The results show that the two trained models agree with labels from human analysts but required only 0.4% of the time. Although the original (human) quality assignments assessed general waveform signal-to-noise, the ANN or RF labels can help facilitate detailed waveform analysis. Our investigations demonstrate the capability of the automated processing using these two ML models to reduce outliers in surface-wave-related measurements without human quality control screening.

58 GEOSCIENCES↗
DOE OSTI2014

A statistical method for retrospective cardiac and respiratory motion gating of interventional cardiac x-ray images

Purpose: Image-guided cardiac interventions involve the use of fluoroscopic images to guide the insertion and movement of interventional devices. Cardiorespiratory gating can be useful for 3D reconstruction from multiple x-ray views and for reducing misalignments between 3D anatomical models overlaid onto fluoroscopy. Methods: The authors propose a novel and potentially clinically useful retrospective cardiorespiratory gating technique. The principal component analysis (PCA) statistical method is used in combination with other image processing operations to make our proposed masked-PCA technique suitable for cardiorespiratory gating. Unlike many previously proposed techniques, our technique is robust to varying image-content, thus it does not require specific catheters or any other optically opaque structures to be visible. Therefore, it works without any knowledge of catheter geometry. The authors demonstrate the application of our technique for the purposes of retrospective cardiorespiratory gating of normal and very low dose x-ray fluoroscopy images. Results: For normal dose x-ray images, the algorithm was validated using 28 clinical electrophysiology x-ray fluoroscopy sequences (2168 frames), from patients who underwent radiofrequency ablation (RFA) procedures for the treatment of atrial fibrillation and cardiac resynchronization therapy procedures for heart failure. The authors established end-systole, end-expiration, and end-inspiration success rates of 97.0%, 97.9%, and 97.0%, respectively. For very low dose applications, the technique was tested on ten x-ray sequences from the RFA procedures with added noise at signal to noise ratio (SNR) values of√(5)0, √(1)0, √(8), √(6), √(5), √(2), and √(1) to simulate the image quality of increasingly lower dose x-ray images. Even at the low SNR value of √(2), representing a dose reduction of more than 25 times, gating success rates of 89.1%, 88.8%, and 86.8% were established. Conclusions: The proposed technique can therefore extract useful information from interventional x-ray images while minimizing exposure to ionizing radiation.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Robust and Simple ADMM Penalty Parameter Selection

We present a new method for online selection of the penalty parameter for the alternating direction method of multipliers (ADMM) algorithm. ADMM is a widely used method for solving a range of optimization problems, including those that arise in signal and image processing. In its standard form, ADMM includes a scalar hyperparameter, known as the penalty parameter, which usually has to be tuned to achieve satisfactory empirical convergence. In this work, we develop a framework for analyzing the ADMM algorithm applied to a quadratic problem as an affine fixed point iteration. Using this framework, we develop a new method for automatically tuning the penalty parameter by detecting when it has become too large or small. We analyze this and several other methods with respect to their theoretical properties, i.e., robustness to problem transformations, and empirical performance on several optimization problems. Our proposed algorithm is based on a theoretical framework with clear, explicit assumptions and approximations, is theoretically covariant/invariant to problem transformations, is simple to implement, and exhibits competitive empirical performance.

42 ENGINEERING↗
DOE OSTI2021

Infrared intrusion detection system (IRIDS)

A system and method for intrusion detection includes an imager directed towards an object in an interior space. The imager is in data communication with a computer. The computer is arranged to process digital three-dimensional image data received from the imager and programmed to execute a change detection algorithm in response to the processed three-dimensional data to determine movement of the object. The computer generates an alarm output in response to detecting movement of the object above a predetermined threshold. The method includes providing an imager directed towards an object in an interior space; receiving Time of Flight signals by the imager; processing digital three-dimensional image data received from the imager; and executing a change detection algorithm in response to the processed three-dimensional data to determine movement of the object.

Russell, John L.↗
DOE OSTI2021

Grand Unification of Quantum Algorithms

Quantum algorithms offer significant speed-ups over their classical counterparts for a variety of problems. The strongest arguments for this advantage are borne by algorithms for quantum search, quantum phase estimation, and Hamiltonian simulation, which appear as subroutines for large families of composite quantum algorithms. A number of these quantum algorithms have recently been tied together by a novel technique known as the quantum singular value transformation (QSVT), which enables one to perform a polynomial transformation of the singular values of a linear operator embedded in a unitary matrix. In the seminal GSLW’19 paper on the QSVT [Gilyén et al., ACM STOC 2019], many algorithms are encompassed, including amplitude amplification, methods for the quantum linear systems problem, and quantum simulation. Here, we provide a pedagogical tutorial through these developments, first illustrating how quantum signal processing may be generalized to the quantum eigenvalue transform, from which the QSVT naturally emerges. Paralleling GSLW’19, we then employ the QSVT to construct intuitive quantum algorithms for search, phase estimation, and Hamiltonian simulation, and also showcase algorithms for the eigenvalue threshold problem and matrix inversion. This overview illustrates how the QSVT is a single framework comprising the three major quantum algorithms, suggesting a grand unification of quantum algorithms.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Search for non-resonant Higgs boson pair production in the $2b+2\ell +{E}_{\textrm{T}}^{\textrm{miss}}$ final state in pp collisions at $\sqrt{s}$ = 13 TeV with the ATLAS detector

A search for non-resonant Higgs boson pair (HH) production is presented, in which one of the Higgs bosons decays to a b-quark pair ($b\bar{b}$) and the other decays to WW * , ZZ * , or τ + τ – , with in each case a final state with ℓ + ℓ – + neutrinos (ℓ = e, μ). The analysis targets separately the gluon-gluon fusion and vector boson fusion production modes. Data recorded by the ATLAS detector in proton-proton collisions at a centre-of-mass energy of 13 TeV at the Large Hadron Collider, corresponding to an integrated luminosity of 140 fb –1 , are used in this analysis. Events are selected to have exactly two b-tagged jets and two leptons with opposite electric charge and missing transverse momentum in the final state. These events are classified using multivariate analysis algorithms to separate the HH events from other Standard Model processes. No evidence of the signal is found. The observed (expected) upper limit on the cross-section for non-resonant Higgs boson pair production is determined to be 9.7 (16.2) times the Standard Model prediction at 95% confidence level. The Higgs boson self-interaction coupling parameter κ λ and the quadrilinear coupling parameter κ 2V are each separately constrained by this analysis to be within the ranges [–6.2, 13.3] and [–0.17, 2.4], respectively, at 95% confidence level, when all other parameters are fixed.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Learning error distribution kernel‐enhanced neural network methodology for multi‐intersection signal control optimization

Traffic congestion has substantially induced significant mobility and energy inefficiency. Many research challenges are identified in traffic signal control and management associated with artificial intelligence (AI)-based models. For example, developing AI-driven dynamic traffic system models that accurately capture high-resolution traffic attributes and formulate robust control algorithms for traffic signal optimization is difficult. Additionally, uncertainties in traffic system modeling and control processes can further complicate traffic signal system controllability. To partially address these challenges, this study presents a novel, hybrid neural network model enhanced with a probability density function kernel shaping technique to formulate traffic system dynamics better and improve comprehensive traffic network modeling and control. The numerical experimental tests were conducted, and the results demonstrate that the proposed control approach outperforms the baseline control strategies and reduces overall average delays by 11.64% on average. By leveraging the capabilities of this innovative model, this study aims to address major challenges related to traffic congestion and energy inefficiency toward more effective and adaptable AI-based traffic control systems.

Wang, Hong [Oak Ridge National Laboratory (ORNL), ↗
NASA NTRS1994

Correlator data analysis for the array feed compensation system

The real-time array feed compensation system is currently being evaluated at DSS 13. This system recovers signal-to-noise ratio (SNR) loss due to mechanical antenna deformations by using an array of seven Ka-band (33.7-GHz) horns to collect the defocused signal fields. The received signals are downconverted and digitized, in-phase and quadrature samples are generated, and combining weights are applied before the samples are recombined. It is shown that when optimum combining weights are employed, the SNR of the combined signal approaches the sum of the channel SNR's. The optimum combining weights are estimated directly from the signals in each channel by the Real-Time Block 2 (RTB2) correlator; since it was designed for very-long-baseline interferometer (VLBI) applications, it can process broadband signals as well as tones to extract the required weight estimates. The estimation algorithms for the optimum combining weights are described for tones and broadband sources. Data recorded in correlator output files can also be used off-line to estimate combiner performance by estimating the SNR in each channel, which was done for data taken during a Jupiter track at DSS 13.

Iijima, B.↗
NASA NTRS1995

Extracting Periodic Signals From Irregularly Sampled Data

Successive approximations formed in Fourier space. Algorithm extracts periodic signals from sparse, irregularly sampled sets of measurement data. Pertains to data processed via fast Fourier transforms (FFTs). Data represents signal components with initially unknown frequencies spanning large spectral range and includes frequencies not integer multiples of minimum FFT frequency.

Wilcox, Jaroslava Z.↗
NASA NTRS2001

Compression of echocardiographic scan line data using wavelet packet transform

An efficient compression strategy is indispensable for digital echocardiography. Previous work has suggested improved results utilizing wavelet transforms in the compression of 2D echocardiographic images. Set partitioning in hierarchical trees (SPIHT) was modified to compress echocardiographic scanline data based on the wavelet packet transform. A compression ratio of at least 94:1 resulted in preserved image quality.

Non-NASA Center↗
NASA NTRS1996

BPSK Demodulation Using Digital Signal Processing

A digital communications signal is a sinusoidal waveform that is modified by a binary (digital) information signal. The sinusoidal waveform is called the carrier. The carrier may be modified in amplitude, frequency, phase, or a combination of these. In this project a binary phase shift keyed (BPSK) signal is the communication signal. In a BPSK signal the phase of the carrier is set to one of two states, 180 degrees apart, by a binary (i.e., 1 or 0) information signal. A digital signal is a sampled version of a "real world" time continuous signal. The digital signal is generated by sampling the continuous signal at discrete points in time. The rate at which the signal is sampled is called the sampling rate (f(s)). The device that performs this operation is called an analog-to-digital (A/D) converter or a digitizer. The digital signal is composed of the sequence of individual values of the sampled BPSK signal. Digital signal processing (DSP) is the modification of the digital signal by mathematical operations. A device that performs this processing is called a digital signal processor. After processing, the digital signal may then be converted back to an analog signal using a digital-to-analog (D/A) converter. The goal of this project is to develop a system that will recover the digital information from a BPSK signal using DSP techniques. The project is broken down into the following steps: (1) Development of the algorithms required to demodulate the BPSK signal; (2) Simulation of the system; and (3) Implementation a BPSK receiver using digital signal processing hardware.

Garcia, Thomas R.↗
DOE OSTI2024

Generalized Quantum Signal Processing

Quantum signal processing (QSP) and quantum singular value transformation (QSVT) currently stand as the most efficient techniques for implementing functions of block-encoded matrices, a central task that lies at the heart of most prominent quantum algorithms. However, current QSP approaches face several challenges, such as the restrictions imposed on the family of achievable polynomials and the difficulty of calculating the required phase angles for specific transformations. In this paper, we present a generalized quantum signal processing (GQSP) approach, employing general SU(2) rotations as our signal-processing operators, rather than relying solely on rotations in a single basis. Our approach lifts all practical restrictions on the family of achievable transformations, with the sole remaining condition being that | P | ≤ 1 , a restriction necessary due to the unitary nature of quantum computation. Furthermore, GQSP provides a straightforward recursive formula for determining the rotation angles needed to construct the polynomials in cases where P and Q are known. In cases where only P is known, we provide an efficient optimization algorithm capable of identifying in under a minute of GPU time, a corresponding Q for polynomials of degree on the order of 10 7 . We further illustrate GQSP simplifies QSP-based strategies for Hamiltonian simulation, offer an optimal solution to the ϵ -approximate fractional query problem that requires O ( ( 1 / δ ) + log ( 1 / ϵ ) ) queries to perform where O ( 1 / δ ) is a proved lower bound, and introduces novel approaches for implementing bosonic operators. Moreover, we propose a novel framework for the implementation of normal matrices, demonstrating its applicability through synthesis of diagonal matrices, as well as the development of a new algorithm for convolution through synthesis of circulant matrices using only O ( d log N + log 2 N ) 1 and 2-qubit gates for a filter of lengths d . Published by the American Physical Society 2024

Motlagh, Danial↗
NASA NTRS2005

Single-Scale Retinex Using Digital Signal Processors

The Retinex is an image enhancement algorithm that improves the brightness, contrast and sharpness of an image. It performs a non-linear spatial/spectral transform that provides simultaneous dynamic range compression and color constancy. It has been used for a wide variety of applications ranging from aviation safety to general purpose photography. Many potential applications require the use of Retinex processing at video frame rates. This is difficult to achieve with general purpose processors because the algorithm contains a large number of complex computations and data transfers. In addition, many of these applications also constrain the potential architectures to embedded processors to save power, weight and cost. Thus we have focused on digital signal processors (DSPs) and field programmable gate arrays (FPGAs) as potential solutions for real-time Retinex processing. In previous efforts we attained a 21 (full) frame per second (fps) processing rate for the single-scale monochromatic Retinex with a TMS320C6711 DSP operating at 150 MHz. This was achieved after several significant code improvements and optimizations. Since then we have migrated our design to the slightly more powerful TMS320C6713 DSP and the fixed point TMS320DM642 DSP. In this paper we briefly discuss the Retinex algorithm, the performance of the algorithm executing on the TMS320C6713 and the TMS320DM642, and compare the results with the TMS320C6711.

Hines, Glenn↗
DOE OSTI2014

SU-D-12A-01: An Inter-Projection Interpolation (IPI) Approach for the Synchronized Moving Grid (SMOG) to Reduce Dose in Cone Beam CT

Purpose: Synchronized moving grid is a promising technique to reduce scatter and ghost artifacts in cone beam computed tomography (CBCT). However, it requires 2 projections in the same gantry angle to obtain full information due to signal blockage by the grid. We proposed an inter-projection interpolation (IPI) method to estimate blocked signals, which may reduce the scan time and the dose. This study aims to provide a framework to achieve a balance between speed, dose and image quality. Methods: The IPI method is based on the hypothesis that an abrupt signal in a projection can be well predicted by the information in the two immediate neighboring projections if the gantry angle step is small. The study was performed on a Catphan and a head phantom. The SMOG was simulated by erasing the information (filling with “0”) of the areas in each projection corresponding to the grid. An IPI algorithm was applied on each projection to recover the erased information. FDK algorithm was used to reconstruct CBCT images for the IPI-processed projections, and compared with the original image in term of signal to noise ratio (SNR) measured in the whole reconstruction image range. The effect of gantry angle step was investigated by comparing the CBCT images from projection sets of various gantry intervals, with IPI-predicted projections to fill the missing projection in the interval. Results: The IPI procession time was 1.79s±0.53s for each projection. SNR after IPI was 29.0db and 28.1db for the Catphan and head phantom, respectively, comparing to 15.3db and 22.7db for an inpainting based interpolation technique. SNR was 28.3, 28.3, 21.8, 19.3 and 17.3 db for gantry angle intervals of 1, 1.5, 2, 2.5 and 3 degrees, respectively. Conclusion: IPI is feasible to estimate the missing information, and achieve an reasonable CBCT image quality with reduced dose and scan time. This study is supported by NIH/NCI grant 1R01CA166948-01.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Synchrophasor Data Correction under GPS Spoofing Attack: A State Estimation-Based Approach

GPS spoofing attack (GSA) has been shown to be one of the most imminent threats to almost all cyber-physical systems incorporated with the civilian GPS signal. Specifically, for our current agenda of the modernization of the power grid, this may greatly jeopardize the benefits provided by the pervasively installed phasor measurement units (PMU). In this paper, we consider the case where synchrophasor data from PMUs are compromised due to the presence of a single GSA, and show that it can be corrected by signal processing techniques. In particular, we introduce a statistical model for synchrophasorbased power system state estimation (SE), and then derive the spoofing-matched algorithms for synchrophasor data correction against GPS spoofing attack. Different testing scenarios in IEEE 14-, 30-, 57-, 118-bus systems are simulated to show the proposed algorithms’ performance on GSA detection and state estimation. Numerical results demonstrate that our proposed algorithms can consistently locate and correct the spoofed synchrophasor data with good accuracy as long as the system observability is satisfied. The accuracy of state estimation is significantly improved compared with the traditional weighted least square method and approaches the performance under the Genie-aided method.

Phasor measurement units, Global Positioning Syste↗
NASA NTRS1983

A sun acquisition sensor for spacecraft guidance and control

The combination of a strap-down analog sun acquisition sensor (AS) and an on-board digital programmable signal processor results in a versatile guidance and control system. The combination can orient the rotation axis of a spin-stabilized spacecraft to the sun no matter what the initial attitude of the spacecraft. During the sun orientation process, spacecraft spin rate can be sensed and supplied as an input to the control algorithm. If needed, the AS-signal processor combination can be used to perform a rhumb-line turn maneuver. In case of unexpected spacecraft operating conditions, or unplanned pointing directions, the signal processor program can be updated via earth-based transmission of another program to cover the new situation. Using only three radiation-hard cadmium-sulfide detectors, containing no moving parts, needing only a few microwatts of power, included in a volume of 550 cubic cm (a redundant pair), and weighing only 540 grams, the AS is a small, simple, sturdy sensing device.

Birnbaum, M. M.↗
NASA NTRS2005

A VHDL Core for Intrinsic Evolution of Discrete Time Filters with Signal Feedback

The design of an Evolvable Machine VHDL Core is presented, representing a discrete-time processing structure capable of supporting control system applications. This VHDL Core is implemented in an FPGA and is interfaced with an evolutionary algorithm implemented in firmware on a Digital Signal Processor (DSP) to create an evolvable system platform. The salient features of this architecture are presented. The capability to implement IIR filter structures is presented along with the results of the intrinsic evolution of a filter. The robustness of the evolved filter design is tested and its unique characteristics are described.

Gwaltney, David A.↗