446,778 research outputs found
Weight Computation of Regular Tree Languages
We present a general framework to define an application-dependent weight
measure on terms that subsumes e.g. total simplification orderings, and an O(n
log n) algorithm for the simultaneous computation of the minimal weight of a
term in the language of each nonterminal of a regular tree grammar, based on
Barzdins' liquid-flow technique.Comment: 26 pages; 3 figures. Originally published 23 Mar 2004 as "FIRST
Reports 1/2004". Section 4 essentially describes Knuth's algorithm from his
paper "A Generalization of Dijkstra's Algorithm" (Information Processing
Letters, Vol.6, No.1, p.1-5, 1977); I wasn't aware of its existence at that
tim
OCR Post-Processing Error Correction Algorithm using Google Online Spelling Suggestion
With the advent of digital optical scanners, a lot of paper-based books,
textbooks, magazines, articles, and documents are being transformed into an
electronic version that can be manipulated by a computer. For this purpose,
OCR, short for Optical Character Recognition was developed to translate scanned
graphical text into editable computer text. Unfortunately, OCR is still
imperfect as it occasionally mis-recognizes letters and falsely identifies
scanned text, leading to misspellings and linguistics errors in the OCR output
text. This paper proposes a post-processing context-based error correction
algorithm for detecting and correcting OCR non-word and real-word errors. The
proposed algorithm is based on Google's online spelling suggestion which
harnesses an internal database containing a huge collection of terms and word
sequences gathered from all over the web, convenient to suggest possible
replacements for words that have been misspelled during the OCR process.
Experiments carried out revealed a significant improvement in OCR error
correction rate. Future research can improve upon the proposed algorithm so
much so that it can be parallelized and executed over multiprocessing
platforms.Comment: LACSC - Lebanese Association for Computational Sciences,
http://www.lacsc.org/; Journal of Emerging Trends in Computing and
Information Sciences, Vol. 3, No. 1, January 201
Flexible Widely-Linear Multi-Branch Decision Feedback Detection Algorithms for Massive MIMO Systems
This paper presents widely-linear multi-branch decision feedback detection
techniques for large-scale multiuser multiple-antenna systems. We consider a
scenario with impairments in the radio-frequency chain in which the in-phase
(I) and quadrature (Q) components exhibit an imbalance, which degrades the
receiver performance and originates non-circular signals. A widely-linear
multi-branch decision feedback receiver is developed to mitigate both the
multiuser interference and the I/Q imbalance effects. An iterative detection
and decoding scheme with the proposed receiver and convolutional codes is also
devised. Simulation results show that the proposed techniques outperform
existing algorithms.Comment: 3 figures, 9 pages. arXiv admin note: text overlap with
arXiv:1308.272
On the Zeros of Ramanujan Filters
Ramanujan filter banks have been used for identifying periodicity structure in streaming data. This letter studies the locations of zeros of Ramanujan filters. All the zeros of Ramanujan filters are shown to lie on or inside the unit circle in the z-plane. A convenient factorization appears as a corollary of this result, which is useful to identify common factors between different Ramanujan filters in a filter bank. For certain families of Ramanujan filters, further structure is identified in the locations of zeros of those filters. It is shown that increasing the number of periods of Ramanujan sums in the filter definition only increases zeros on the unit circle in z -plane. A potential application of these results is that by identifying common factors between Ramanujan filters, one can obtain efficient implementations of Ramanujan filter banks (RFB) as demonstrated here
Study of Robust Distributed Beamforming Based on Cross-Correlation and Subspace Projection Techniques
In this work, we present a novel robust distributed beamforming (RDB)
approach to mitigate the effects of channel errors on wireless networks
equipped with relays based on the exploitation of the cross-correlation between
the received data from the relays at the destination and the system output. The
proposed RDB method, denoted cross-correlation and subspace projection (CCSP)
RDB, considers a total relay transmit power constraint in the system and the
objective of maximizing the output signal-to-interference-plus-noise ratio
(SINR). The relay nodes are equipped with an amplify-and-forward (AF) protocol
and we assume that the channel state information (CSI) is imperfectly known at
the relays and there is no direct link between the sources and the destination.
The CCSP does not require any costly optimization procedure and simulations
show an excellent performance as compared to previously reported algorithms.Comment: 3 figures, 7 pages. arXiv admin note: text overlap with
arXiv:1707.00953
Study of Joint MSINR and Relay Selection Algorithms for Distributed Beamforming
This paper presents joint maximum signal-to-interference-plus-noise ratio
(MSINR) and relay selection algorithms for distributed beamforming. We propose
a joint MSINR and restricted greedy search relay selection (RGSRS) algorithm
with a total relay transmit power constraint that iteratively optimizes both
the beamforming weights at the relays nodes, maximizing the SINR at the
destination. Specifically, we devise a relay selection scheme that based on
greedy search and compare it to other schemes like restricted random relay
selection (RRRS) and restricted exhaustive search relay selection (RESRS). A
complexity analysis is provided and simulation results show that the proposed
joint MSINR and RGSRS algorithm achieves excellent bit error rate (BER) and
SINR performances.Comment: 7 pages, 2 figures. arXiv admin note: text overlap with
arXiv:1707.0095
High-speed Implementation of FFT-based Privacy Amplification on FPGA in Quantum Key Distribution
Privacy amplification (PA) is a vital procedure in quantum key distribution
(QKD) to generate the secret key that the eavesdropper has only negligible
information from the identical correcting key for the communicating parties.
With the increase of repeat frequency of discrete-variable QKD (DV-QKD) system,
the processing speed of PA has become the bottle neck restricting DV-QKD's
secure key rate. The PA using Toeplitz-based Hash function is adopted widely
because of its simplicity and parallel feature. Because this algorithm can be
accelerated with Fast Fourier Transform (FFT), an improved scheme PA for
Field-programmable Gate Array (FPGA) based on this is proposed. This paper
improves the custom FFT-based algorithm by reducing the number of computations
and read/write memory operations significantly. The correctness is verified
when implemented in a Xilinx Virtex-6 FPGA. Meanwhile, the processing speed of
improved scheme can nearly double the classical Toeplitz Hashing scheme on FPGA
through the actual experiment.Comment: 11 pages, 6 figure
Study of BEM-Type Channel Estimation Techniques for 5G Multicarrier Systems
In this paper, we investigate channel estimation techniques for 5G
multicarrier systems. Due to the characteristics of the 5G application
scenarios, channel estimation techniques have been tested in Orthogonal
Frequency Division Multiplexing (OFDM) and Generalized Frequency Division
Multiplexing (GFDM) systems. The orthogonality between subcarriers in OFDM
systems permits inserting and extracting pilots without interference. However,
due to pulse shaping, subcarriers in GFDM are no longer orthogonal and
interfere with each other. Due to such interference, the channel estimation for
GFDM is not trivial. A robust and low-complexity channel estimator can be
obtained by combining a minimum mean-square error (MMSE) regularization and the
basis expansion model (BEM) approach. In this work, we develop a BEM-type
channel estimator along with a strategy to obtain the covariance matrix of the
BEM coefficients. Simulations show that the BEM-type channel estimation shows
performance close to that of the linear MMSE (LMMSE), even though there is no
need to know the channel power delay profile, and its complexity is low.Comment: 2 figures, 7 page
UNIQUE: Unsupervised Image Quality Estimation
In this paper, we estimate perceived image quality using sparse
representations obtained from generic image databases through an unsupervised
learning approach. A color space transformation, a mean subtraction, and a
whitening operation are used to enhance descriptiveness of images by reducing
spatial redundancy; a linear decoder is used to obtain sparse representations;
and a thresholding stage is used to formulate suppression mechanisms in a
visual system. A linear decoder is trained with 7 GB worth of data, which
corresponds to 100,000 8x8 image patches randomly obtained from nearly 1,000
images in the ImageNet 2013 database. A patch-wise training approach is
preferred to maintain local information. The proposed quality estimator UNIQUE
is tested on the LIVE, the Multiply Distorted LIVE, and the TID 2013 databases
and compared with thirteen quality estimators. Experimental results show that
UNIQUE is generally a top performing quality estimator in terms of accuracy,
consistency, linearity, and monotonic behavior.Comment: 12 pages, 5 figures, 2 table
Study of Switched Max-Link Buffer-Aided Relay Selection for Cooperative MIMO Systems
In this paper, we investigate relay selection for cooperative
multiple-antenna systems that are equipped with buffers, which increase the
reliability of wireless links. In particular, we present a novel relay
selection technique based on switching and the Max-Link protocol that is named
Switched Max-Link. We also introduce a novel relay selection criterion based on
the maximum likelihood (ML) principle denoted maximum minimum distance that is
incorporated into. Simulations are then employed to evaluate the performance of
the proposed and existing techniques.Comment: 8 pages, 3 figures. arXiv admin note: text overlap with
arXiv:1707.0095
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