4,901 research outputs found
Analysis and application of digital spectral warping in analog and mixed-signal testing
Spectral warping is a digital signal processing transform which shifts the frequencies contained within a signal along the frequency axis. The Fourier transform coefficients of a warped signal correspond to frequency-domain 'samples' of the original signal which are unevenly spaced along the frequency axis. This property allows the technique to be efficiently used for DSP-based analog and mixed-signal testing. The analysis and application of spectral warping for test signal generation, response analysis, filter design, frequency response evaluation, etc. are discussed in this paper along with examples of the software and hardware implementation
G Electronics and Data Acquisition (Forward-Angle Measurements)
The G parity-violation experiment at Jefferson Lab (Newport News, VA) is
designed to determine the contribution of strange/anti-strange quark pairs to
the intrinsic properties of the proton. In the forward-angle part of the
experiment, the asymmetry in the cross section was measured for
elastic scattering by counting the recoil protons corresponding to the two
beam-helicity states. Due to the high accuracy required on the asymmetry, the
G experiment was based on a custom experimental setup with its own
associated electronics and data acquisition (DAQ) system. Highly specialized
time-encoding electronics provided time-of-flight spectra for each detector for
each helicity state. More conventional electronics was used for monitoring
(mainly FastBus). The time-encoding electronics and the DAQ system have been
designed to handle events at a mean rate of 2 MHz per detector with low
deadtime and to minimize helicity-correlated systematic errors. In this paper,
we outline the general architecture and the main features of the electronics
and the DAQ system dedicated to G forward-angle measurements.Comment: 35 pages. 17 figures. This article is to be submitted to NIM section
A. It has been written with Latex using \documentclass{elsart}. Nuclear
Instruments and Methods in Physics Research Section A: Accelerators,
Spectrometers, Detectors and Associated Equipment In Press (2007
Graph Signal Processing: Overview, Challenges and Applications
Research in Graph Signal Processing (GSP) aims to develop tools for
processing data defined on irregular graph domains. In this paper we first
provide an overview of core ideas in GSP and their connection to conventional
digital signal processing. We then summarize recent developments in developing
basic GSP tools, including methods for sampling, filtering or graph learning.
Next, we review progress in several application areas using GSP, including
processing and analysis of sensor network data, biological data, and
applications to image processing and machine learning. We finish by providing a
brief historical perspective to highlight how concepts recently developed in
GSP build on top of prior research in other areas.Comment: To appear, Proceedings of the IEE
Handheld-Impedance-Measurement System with seven-decade capability and potentiostatic function
This paper describes design and test of a new impedance-measurement system for nonlinear devices that exhibits a seven-decade range and works down to a frequency of 0.01 Hz. The system is specifically designed for electrochemical measurements, but the proposed architecture can be employed in many other fields where flexible signal generation and analysis are required. The system employs an unconventional signal generator based on two pulsewidth modulation (PWM) oscillators and an autocalibration system that allows uncertainties of less than 3% to be obtained over a range of 1 kΩ to 100 GΩ. A synchronous demodulation processing allows the noise superimposed to the low-amplitude input signals to be made negligibl
mmWave Massive MIMO with Simple RF and Appropriate DSP
There is considerable interest in the combined use of millimeter-wave
(mmwave) frequencies and arrays of massive numbers of antennas (massive MIMO)
for next-generation wireless communications systems. A symbiotic relationship
exists between these two factors: mmwave frequencies allow for densely packed
antenna arrays, and hence massive MIMO can be achieved with a small form
factor; low per-antenna SNR and shadowing can be overcome with a large array
gain; steering narrow beams or nulls with a large array is a good match for the
line-of-sight (LOS) or near-LOS mmwave propagation environments, etc.. However,
the cost and power consumption for standard implementations of massive MIMO
arrays at mmwave frequencies is a significant drawback to rapid adoption and
deployment. In this paper, we examine a number of possible approaches to reduce
cost and power at both the basestation and user terminal, making up for it with
signal processing and additional (cheap) antennas. These approaches include
lowresolution Analog-to-Digital Converters (ADCs), wireless local oscillator
distribution networks, spatial multiplexing and multistreaming instead of
higher-order modulation etc.. We will examine the potential of these approaches
in making mmwave massive MIMO a reality and discuss the requirements in terms
of digital signal processing (DSP).Comment: published in Asilomar 201
A Polyphase Multipath Technique for Software-Defined Radio Transmitters
Transmitter circuits using large signal swings and hard-switched mixers are power-efficient, but also produce unwanted harmonics and sidebands, which are commonly removed using dedicated filters. This paper presents a polyphase multipath technique to relax or eliminate filters by canceling a multitude of harmonics and sidebands. Using this technique, a wideband and flexible power upconverter with a clean output spectrum is realized in 0.13-mum CMOS, aiming at a software-defined radio application. Prototype chips operate from DC to 2.4 GHz with spurs smaller than -40 dBc up to the 17th harmonic (18-path mode) or 5th harmonic (6-path mode) of the transmit frequency, without tuning or calibration. The transmitter delivers 8 mW of power to a 100-Omega load (2.54 Vpp-diff voltage swing) and the complete chip consumes 228 mW from a 1.2-V supply. It uses no filters, but only digital circuits and mixer
Reliable Linear, Sesquilinear and Bijective Operations On Integer Data Streams Via Numerical Entanglement
A new technique is proposed for fault-tolerant linear, sesquilinear and
bijective (LSB) operations on integer data streams (), such as:
scaling, additions/subtractions, inner or outer vector products, permutations
and convolutions. In the proposed method, the input integer data streams
are linearly superimposed to form numerically-entangled integer data
streams that are stored in-place of the original inputs. A series of LSB
operations can then be performed directly using these entangled data streams.
The results are extracted from the entangled output streams by additions
and arithmetic shifts. Any soft errors affecting any single disentangled output
stream are guaranteed to be detectable via a specific post-computation
reliability check. In addition, when utilizing a separate processor core for
each of the streams, the proposed approach can recover all outputs after
any single fail-stop failure. Importantly, unlike algorithm-based fault
tolerance (ABFT) methods, the number of operations required for the
entanglement, extraction and validation of the results is linearly related to
the number of the inputs and does not depend on the complexity of the performed
LSB operations. We have validated our proposal in an Intel processor (Haswell
architecture with AVX2 support) via fast Fourier transforms, circular
convolutions, and matrix multiplication operations. Our analysis and
experiments reveal that the proposed approach incurs between to
reduction in processing throughput for a wide variety of LSB operations. This
overhead is 5 to 1000 times smaller than that of the equivalent ABFT method
that uses a checksum stream. Thus, our proposal can be used in fault-generating
processor hardware or safety-critical applications, where high reliability is
required without the cost of ABFT or modular redundancy.Comment: to appear in IEEE Trans. on Signal Processing, 201
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