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Duplicate detection for symbolically compressed documents

Proceedings of the Fifth International Conference on Document Analysis and Recognition. ICDAR '99 (Cat. No.PR00318), 1999
A new family of symbolic compression algorithms has recently been developed that includes the ongoing JBIG2 standardization effort as well as related commercial products. These techniques are specifically designed for binary document images. They cluster individual blobs in a document and store the sequence of occurrence of blobs and representative ...
null Dar-Shyang Lee, J.J. Hull
openaire   +1 more source

Deep Learning-Based Joint Symbol Detection for NOMA

Signal Processing and Communications Applications Conference, 2019
—Non-orthogonal multiple access is one of the most important candidates for next-generation communication systems called 5G and beyond. NOMA provides superiority to multiple access techniques that has been used up to recent times in terms of outage ...
A. Emir, F. Kara, Hakan Kaya
semanticscholar   +1 more source

Edge detection using optical symbolic substitution

Optics Communications, 1989
Abstract Optical symbolic substitution architectures based on phase-only hologram and content-addressable memory are used for digital- optical edge detection. Accordingly, symbolic substitution rules for phase-only hologram based optical computing system and reduced minterms for content-addressable memory based optical computing system are determined
Abdallah K. Cherri, Mohammad A. Karim
openaire   +1 more source

Low-complexity joint channel estimation and symbol detection for OFDMA systems

China Communications, 2019
In this paper, we propose a joint channel estimation and symbol detection (JCESD) algorithm relying on message-passing algorithms (MPA) for orthogonal frequency division multiple access (OFDMA) systems.
Rui Xin   +4 more
semanticscholar   +1 more source

Detecting hidden periodicities on symbolic sequences

Journal of Interdisciplinary Mathematics, 2009
Abstract The aim of this work is to provide detectors for hidden periodicity and latent periodicity on symbolic sequences. Our detectors come from a decision making process based on a statistical threshold mechanism, derived from DeMoivre-Lagrange Theorem for binomial distributions.
openaire   +1 more source

Iterative Symbol-by-symbol Decision Feedback Detection for MIMO-ISI Channels

APCCAS 2006 - 2006 IEEE Asia Pacific Conference on Circuits and Systems, 2006
This paper investigates the decision feedback detection for intersymbol interference multiple-input multiple-output (MIMO-ISI) channels. Firstly, a constrained symbol-by-symbol decision feedback detector (CS-DFD) is presented, in which a fixed constraint is used to mitigate the error propagation.
Xuan Huan Nguyen, Jinho Choi
openaire   +1 more source

SORN Arithmetic for MIMO Symbol Detection - Exploration of the Type-2 Unum Format

IEEE International New Circuits and Systems Conference, 2019
In this paper a new approach for a fast and low-precision number format is explored. The SORN representation uses a fixed set of exact values and open intervals in between to represent real numbers on the digital layer.
Moritz Bärthel   +3 more
semanticscholar   +1 more source

Near-optimal symbol-by-symbol detection schemes for flat Rayleigh fading

1994 IEEE GLOBECOM. Communications: The Global Bridge, 1995
The optimal MAP detection algorithm for demodulation of M-QAM signaling in the frequency flat Rayleigh fading channel is proposed. A recursive structure is derived which allows for symbol-by-symbol metrics to be computed and data decisions to be made in an efficient manner.
J.P. Seymour, M.P. Fitz
openaire   +1 more source

Symbol Detection in High Speed Channels

2016
Mobile wireless communication channels are characterized by time-varying multipath propagation [1], that is, due to multiple scatterers, the electromagnetic signal can propagate along several different paths which causes frequency-selectivity and time-selectivity.
openaire   +1 more source

Towards fully automated processing and analysis of construction diagrams: AI-powered symbol detection

International Journal on Document Analysis and Recognition
Laura Jamieson   +2 more
semanticscholar   +1 more source

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