68,665 research outputs found
Astronomical verification of a stabilized frequency reference transfer system for the Square Kilometre Array
In order to meet its cutting-edge scientific objectives, the Square Kilometre
Array (SKA) telescope requires high-precision frequency references to be
distributed to each of its antennas. The frequency references are distributed
via fiber-optic links and must be actively stabilized to compensate for
phase-noise imposed on the signals by environmental perturbations on the links.
SKA engineering requirements demand that any proposed frequency reference
distribution system be proved in "astronomical verification" tests. We present
results of the astronomical verification of a stabilized frequency reference
transfer system proposed for SKA-mid. The dual-receiver architecture of the
Australia Telescope Compact Array was exploited to subtract the phase-noise of
the sky signal from the data, allowing the phase-noise of observations
performed using a standard frequency reference, as well as the stabilized
frequency reference transfer system transmitting over 77 km of fiber-optic
cable, to be directly compared. Results are presented for the fractional
frequency stability and phase-drift of the stabilized frequency reference
transfer system for celestial calibrator observations at 5 GHz and 25 GHz.
These observations plus additional laboratory results for the transferred
signal stability over a 166 km metropolitan fiber-optic link are used to show
that the stabilized transfer system under test exceeds all SKA phase-stability
requirements under a broad range of observing conditions. Furthermore, we have
shown that alternative reference dissemination systems that use multiple
synthesizers to supply reference signals to sub-sections of an array may limit
the imaging capability of the telescope.Comment: 12 pages, accepted to The Astronomical Journa
Color-decoupled photo response non-uniformity for digital image forensics
The last few years have seen the use of photo response non-uniformity noise (PRNU), a unique fingerprint of imaging sensors, in various digital forensic applications such as source device identification, content integrity verification and authentication. However, the use of a colour filter array for capturing only one of the three colour components per pixel introduces colour interpolation noise, while the existing methods for extracting PRNU provide no effective means for addressing this issue. Because the artificial colours obtained through the colour interpolation process is not directly acquired from the scene by physical hardware, we expect that the PRNU extracted from the physical components, which are free from interpolation noise, should be more reliable than that from the artificial channels, which carry interpolation noise. Based on this assumption we propose a Couple-Decoupled PRNU (CD-PRNU) extraction method, which first decomposes each colour channel into 4 sub-images and then extracts the PRNU noise from each sub-image. The PRNU noise patterns of the sub-images are then assembled to get the CD-PRNU. This new method can prevent the interpolation noise from propagating into the physical components, thus improving the accuracy of device identification and image content integrity verification
On the Verification of a WiMax Design Using Symbolic Simulation
In top-down multi-level design methodologies, design descriptions at higher
levels of abstraction are incrementally refined to the final realizations.
Simulation based techniques have traditionally been used to verify that such
model refinements do not change the design functionality. Unfortunately, with
computer simulations it is not possible to completely check that a design
transformation is correct in a reasonable amount of time, as the number of test
patterns required to do so increase exponentially with the number of system
state variables. In this paper, we propose a methodology for the verification
of conformance of models generated at higher levels of abstraction in the
design process to the design specifications. We model the system behavior using
sequence of recurrence equations. We then use symbolic simulation together with
equivalence checking and property checking techniques for design verification.
Using our proposed method, we have verified the equivalence of three WiMax
system models at different levels of design abstraction, and the correctness of
various system properties on those models. Our symbolic modeling and
verification experiments show that the proposed verification methodology
provides performance advantage over its numerical counterpart.Comment: In Proceedings SCSS 2012, arXiv:1307.802
Time-Contrastive Learning Based Deep Bottleneck Features for Text-Dependent Speaker Verification
There are a number of studies about extraction of bottleneck (BN) features
from deep neural networks (DNNs)trained to discriminate speakers, pass-phrases
and triphone states for improving the performance of text-dependent speaker
verification (TD-SV). However, a moderate success has been achieved. A recent
study [1] presented a time contrastive learning (TCL) concept to explore the
non-stationarity of brain signals for classification of brain states. Speech
signals have similar non-stationarity property, and TCL further has the
advantage of having no need for labeled data. We therefore present a TCL based
BN feature extraction method. The method uniformly partitions each speech
utterance in a training dataset into a predefined number of multi-frame
segments. Each segment in an utterance corresponds to one class, and class
labels are shared across utterances. DNNs are then trained to discriminate all
speech frames among the classes to exploit the temporal structure of speech. In
addition, we propose a segment-based unsupervised clustering algorithm to
re-assign class labels to the segments. TD-SV experiments were conducted on the
RedDots challenge database. The TCL-DNNs were trained using speech data of
fixed pass-phrases that were excluded from the TD-SV evaluation set, so the
learned features can be considered phrase-independent. We compare the
performance of the proposed TCL bottleneck (BN) feature with those of
short-time cepstral features and BN features extracted from DNNs discriminating
speakers, pass-phrases, speaker+pass-phrase, as well as monophones whose labels
and boundaries are generated by three different automatic speech recognition
(ASR) systems. Experimental results show that the proposed TCL-BN outperforms
cepstral features and speaker+pass-phrase discriminant BN features, and its
performance is on par with those of ASR derived BN features. Moreover,....Comment: Copyright (c) 2019 IEEE. Personal use of this material is permitted.
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WaveCNV: allele-specific copy number alterations in primary tumors and xenograft models from next-generation sequencing.
MotivationCopy number variations (CNVs) are a major source of genomic variability and are especially significant in cancer. Until recently microarray technologies have been used to characterize CNVs in genomes. However, advances in next-generation sequencing technology offer significant opportunities to deduce copy number directly from genome sequencing data. Unfortunately cancer genomes differ from normal genomes in several aspects that make them far less amenable to copy number detection. For example, cancer genomes are often aneuploid and an admixture of diploid/non-tumor cell fractions. Also patient-derived xenograft models can be laden with mouse contamination that strongly affects accurate assignment of copy number. Hence, there is a need to develop analytical tools that can take into account cancer-specific parameters for detecting CNVs directly from genome sequencing data.ResultsWe have developed WaveCNV, a software package to identify copy number alterations by detecting breakpoints of CNVs using translation-invariant discrete wavelet transforms and assign digitized copy numbers to each event using next-generation sequencing data. We also assign alleles specifying the chromosomal ratio following duplication/loss. We verified copy number calls using both microarray (correlation coefficient 0.97) and quantitative polymerase chain reaction (correlation coefficient 0.94) and found them to be highly concordant. We demonstrate its utility in pancreatic primary and xenograft sequencing data.Availability and implementationSource code and executables are available at https://github.com/WaveCNV. The segmentation algorithm is implemented in MATLAB, and copy number assignment is implemented [email protected] informationSupplementary data are available at Bioinformatics online
A Software-Defined-Radio Platform for Multiple-Input-Multiple-Output Over-The-Air Measurement
This paper presents a 2 × 2 multiple-inputmultiple-output over-the-air (MIMO OTA) measurement system with user-programmable, reconfigurable and real-time signal processing field-programmable gate arrays (FPGAs)-based software-defined radio (SDR) capability. Signal generation and analysis as well as channel emulation are all implemented using vector signal transceivers (VSTs). As a demonstration, we performed the Third Generation Partnership Project (3GPP) two-stage MIMO OTA conducted test using a downlink time division long-term evolution (TD-LTE) duplex scheme. The channel emulation was operated in a stochastic mode. Some preliminary results of the system verification are shown
A Benes Based NoC Switching Architecture for Mixed Criticality Embedded Systems
Multi-core, Mixed Criticality Embedded (MCE) real-time systems require high
timing precision and predictability to guarantee there will be no interference
between tasks. These guarantees are necessary in application areas such as
avionics and automotive, where task interference or missed deadlines could be
catastrophic, and safety requirements are strict. In modern multi-core systems,
the interconnect becomes a potential point of uncertainty, introducing major
challenges in proving behaviour is always within specified constraints,
limiting the means of growing system performance to add more tasks, or provide
more computational resources to existing tasks.
We present MCENoC, a Network-on-Chip (NoC) switching architecture that
provides innovations to overcome this with predictable, formally verifiable
timing behaviour that is consistent across the whole NoC. We show how the
fundamental properties of Benes networks benefit MCE applications and meet our
architecture requirements. Using SystemVerilog Assertions (SVA), formal
properties are defined that aid the refinement of the specification of the
design as well as enabling the implementation to be exhaustively formally
verified. We demonstrate the performance of the design in terms of size,
throughput and predictability, and discuss the application level considerations
needed to exploit this architecture
Predictive biometrics: A review and analysis of predicting personal characteristics from biometric data
Interest in the exploitation of soft biometrics information has continued to develop over the last decade or so. In comparison with traditional biometrics, which focuses principally on person identification, the idea of soft biometrics processing is to study the utilisation of more general information regarding a system user, which is not necessarily unique. There are increasing indications that this type of data will have great value in providing complementary information for user authentication. However, the authors have also seen a growing interest in broadening the predictive capabilities of biometric data, encompassing both easily definable characteristics such as subject age and, most recently, `higher level' characteristics such as emotional or mental states. This study will present a selective review of the predictive capabilities, in the widest sense, of biometric data processing, providing an analysis of the key issues still adequately to be addressed if this concept of predictive biometrics is to be fully exploited in the future
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