Compression and Modulation

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Full List of Titles
1: Speech Processing
CELP Coding
Large Vocabulary Recognition
Speech Analysis and Enhancement
Acoustic Modeling I
ASR Systems and Applications
Topics in Speech Coding
Speech Analysis
Low Bit Rate Speech Coding I
Robust Speech Recognition in Noisy Environments
Speaker Recognition
Acoustic Modeling II
Speech Production and Synthesis
Feature Extraction
Robust Speech Recognition and Adaptation
Low Bit Rate Speech Coding II
Speech Understanding
Language Modeling I
2: Speech Processing, Audio and Electroacoustics, and Neural Networks
Acoustic Modeling III
Lexical Issues/Search
Speech Understanding and Systems
Speech Analysis and Quantization
Utterance Verification/Acoustic Modeling
Language Modeling II
Adaptation /Normalization
Speech Enhancement
Topics in Speaker and Language Recognition
Echo Cancellation and Noise Control
Coding
Auditory Modeling, Hearing Aids and Applications of Signal Processing to Audio and Acoustics
Spatial Audio
Music Applications
Application - Pattern Recognition & Speech Processing
Theory & Neural Architecture
Signal Separation
Application - Image & Nonlinear Signal Processing
3: Signal Processing Theory & Methods I
Filter Design and Structures
Detection
Wavelets
Adaptive Filtering: Applications and Implementation
Nonlinear Signals and Systems
Time/Frequency and Time/Scale Analysis
Signal Modeling and Representation
Filterbank and Wavelet Applications
Source and Signal Separation
Filterbanks
Emerging Applications and Fast Algorithms
Frequency and Phase Estimation
Spectral Analysis and Higher Order Statistics
Signal Reconstruction
Adaptive Filter Analysis
Transforms and Statistical Estimation
Markov and Bayesian Estimation and Classification
4: Signal Processing Theory & Methods II, Design and Implementation of Signal Processing Systems, Special Sessions, and Industry Technology Tracks
System Identification, Equalization, and Noise Suppression
Parameter Estimation
Adaptive Filters: Algorithms and Performance
DSP Development Tools
VLSI Building Blocks
DSP Architectures
DSP System Design
Education
Recent Advances in Sampling Theory and Applications
Steganography: Information Embedding, Digital Watermarking, and Data Hiding
Speech Under Stress
Physics-Based Signal Processing
DSP Chips, Architectures and Implementations
DSP Tools and Rapid Prototyping
Communication Technologies
Image and Video Technologies
Automotive Applications / Industrial Signal Processing
Speech and Audio Technologies
Defense and Security Applications
Biomedical Applications
Voice and Media Processing
Adaptive Interference Cancellation
5: Communications, Sensor Array and Multichannel
Source Coding and Compression
Compression and Modulation
Channel Estimation and Equalization
Blind Multiuser Communications
Signal Processing for Communications I
CDMA and Space-Time Processing
Time-Varying Channels and Self-Recovering Receivers
Signal Processing for Communications II
Blind CDMA and Multi-Channel Equalization
Multicarrier Communications
Detection, Classification, Localization, and Tracking
Radar and Sonar Signal Processing
Array Processing: Direction Finding
Array Processing Applications I
Blind Identification, Separation, and Equalization
Antenna Arrays for Communications
Array Processing Applications II
6: Multimedia Signal Processing, Image and Multidimensional Signal Processing, Digital Signal Processing Education
Multimedia Analysis and Retrieval
Audio and Video Processing for Multimedia Applications
Advanced Techniques in Multimedia
Video Compression and Processing
Image Coding
Transform Techniques
Restoration and Estimation
Image Analysis
Object Identification and Tracking
Motion Estimation
Medical Imaging
Image and Multidimensional Signal Processing Applications I
Segmentation
Image and Multidimensional Signal Processing Applications II
Facial Recognition and Analysis
Digital Signal Processing Education

Author Index
A B C D E F G H I
J K L M N O P Q R
S T U V W X Y Z

Method of Optimal Directions for Frame Design

Authors:

Kjersti Engan,
Sven Ole Aase,
John Haakon Husøy,

Page (NA) Paper number 1204

Abstract:

A frame design technique for use with vector selection algorithms, for example Matching Pursuits (MP), is presented. The design algorithm is iterative and requires a training set of signal vectors. The algorithm, called Method of Optimal Directions (MOD), is an improvement of the algorithm presented in [1]. The MOD is applied to speech and electrocardiogram (ECG) signals, and the designed frames are tested on signals outside the training sets. Experiments demonstrate that the approximation capabilities, in terms of mean squared error (MSE), of the optimized frames are significantly better than those obtained using frames designed by the algorithm in [1]. Experiments show typical reduction in MSE by 20-50%.

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Performance of Ordered Statistics Decoding for Robust Video Transmission on the WSSUS Channel

Authors:

Wu-Hsiang Jonas Chen,
Jenq-Neng Hwang,

Page (NA) Paper number 1808

Abstract:

This paper investigates the performance of ordered statistics decoding of linear block codes with binary differential phase-shift-keying (2DPSK) transmission on the wide-sense-stationary uncorrelated-scattering (WSSUS) Rayleigh fading channel. For typical mobile speed 60 mph, tropospheric scatter radio communication at carrier frequency 900 MHz and very low bit rate video communication at transmission speed 32 kbit/s, the channel is modeled as a frequency non-selective, slow fading environment without inter-symbol interference (ISI). At bit error rate (BER) 10^(-5), 34.5 dB and 38 dB gains compared to uncoded 2DPSK are obtained for the decoding of the (24, 12, 8) extended Golay code and the (128, 64, 22) extended BCH code with sufficient degree of interleaving.

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Joint Source-Channel Decoding for Variable-Length Encoded Data by Exact and Approximate MAP Sequence Estimation

Authors:

MoonSeo Park,
David J Miller,

Page (NA) Paper number 2064

Abstract:

Joint source-channel decoding based on residual source redundancy is an effective paradigm for error-resilient data compression. While previous work only considered fixed rate systems, the extension of these techniques for variable-length encoded data was recently independently proposed by the authors [6],[7] and by Demir and Sayood [1]. In this paper, we describe and compare the performance of a computationally complex exact maximum a posteriori (MAP) decoder [6], [7], its efficient approximation [6], [7], an alternative approximate MAP decoder [1], and an improved version of this decoder suggested here. Moreover, we evaluate several source and channel coding configurations. Our results show that the approximate MAP technique from [6], [7] outperforms other approximate methods and provides substantial error protection to variable-length encoded data.

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Gaussian Modeling For Channel Errors Diagnosis In Image Transmission

Authors:

Fabrice Labeau,
Luc Vandendorpe,
Beno^it Macq,

Page (NA) Paper number 1284

Abstract:

In this paper we propose an original study of the reconstruction of subband compressed images impaired by channel transmission errors. The method proceeds in two steps : first a detection scheme is applied to determine which coefficients of the subband decomposition have been affected by transmission, and then an estimation step tries to evaluate the erroneous coefficients. In our model, subband coefficients are considered to be drawn from jointly gaussian random processes. Based on this assumption, conditional statistics can be computed which enable to test the likelihood of a given set of received coefficients with respect to the rest of the image. The detection and estimation processes are derived from these statistics. The method is validated through simulation and visual results are provided. The drawbacks of the method are outlined and explained through the discrepancies between the gaussian assumption and real world images, namely around image edges.

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The Application Of Walsh Transform For Forward Error Correction

Authors:

Man Hung,
Farokh A Marvasti,
Mohammad Reza Nakhai,

Page (NA) Paper number 1072

Abstract:

In this paper, we present a novel class of forward error correcting codes constructed using the discrete Walsh transform. They are a class of double-error correcting codes defined on the field of real numbers. An iterative decoding algorithm for Walsh transform codes is developed and implemented. The error correcting performance of Walsh transform codes over an AWGN channel is evaluated. Selected Walsh transform code parameters are compared to those of the well-known BCH codes.

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Modulating Waveforms for OFDM

Authors:

Zoran D Cvetković,

Page (NA) Paper number 2181

Abstract:

Orthogonal frequency division multiplexing (OFDM) is a popular transmission technique that is employed in applications such as Digital Audio Broadcasting, Asymmetric Digital Subscriber Line and wireless LAN. In this work we consider design of modulating waveforms for OFDM in the presence of delay spread and system impairments such as frequency offset and jitter. We give a complete parameterization of OFDM modulating waveforms. Increasing robustness of OFDM to frequency offsets requires using long modulating waveforms. To make implementation of OFDM systems with long modulating waveforms feasible we propose fast implementation algorithms. Some preliminary modulating waveform design examples are presented. The presented waveforms demonstrate that robustness of OFDM systems to impairments can be improved by allowing certain degradation of unnecessarily good performance of the state of the art OFDM systems in ideal operating conditions.

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Efficient Method for Carrier Offset Correction in OFDM System

Authors:

Hongya Ge, New Jersey Institute of Technology, Newark, NJ 07102, USA. (USA)
Kun Wang,

Page (NA) Paper number 2466

Abstract:

In this work, we present a simple approach to estimate and correct the carrier offset in an orthogonal frequency division multiplexing(OFDM) system. The approach leads to a computationally and statistically efficient estimator for the carrier offset. Computer simulations verify that the estimation accuracy is comparable to the Cramer-Rao bound(CRB). We demonstrated that by incorporating the estimated carrier offset(obtained using reasonable frames of OFDM data) in the demodulation process, the bit-error-rate(BER) can approach that of the ideal OFDM system with no carrier offset.

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Classification of Modulation Modes Using Time-Frequency Methods

Authors:

Helmut Ketterer,
Friedrich Jondral,
Antonio H Costa,

Page (NA) Paper number 1408

Abstract:

This paper proposes a new technique for feature extraction of modulated signals which is based on a pattern recognition approach. The new algorithm uses the cross Margenau-Hill distribution, autoregressive modeling, and amplitude variations to detect phase shifts, frequency shifts, and amplitude shifts, respectively. Our method is capable of classifying PSK2, PSK4, PSK8, PSK16, FSK2, FSK4, QAM8 and OOK signals. Unlike most of the existing decision- theoretic approaches, no explicit a priori information is required by our algorithm. Consequently, the method is suitable for application in a general non- cooperative environment. Furthermore, our approach is computationally inexpensive. Simulation results on both synthetic and "real world" short-wave signals show that our approach is robust against noise up to a signal-to- noise ratio (SNR) of approximately 10 dB. A success rate greater than 94 percent is obtained.

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Pulse Train Deinterleaving: Algorithms and Cost Criteria

Authors:

Keith S.M. Lee,
Michael J. Rowe,
Vikram Krishnamurthy,

Page (NA) Paper number 1410

Abstract:

Consider the problem where pulse trains transmitted from a known number of sources are received on a single communications channel. These pulses are corrupted with noise. The deinterleaving problem is to determine which source contributed which pulse and the periods and phases of each source. This paper explores the performance of a number of deinterleaving algorithms. We propose an alternative to the existing forward dynamic programming (FDP) technique: simulated annealing (SA). It can use either the same cost function as for FDP, or an L1 or L2 norm output error cost function. We also investigate modelling the noise by heavy-tailed distributions, in addition to white Gaussian noise (WGN).

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