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The present paper has considered multithreshold decoders for self-orthogonal codes providing a near-optimal efficiency of the error correction under linear computational complexity. New divergence principle used within construction and decoding convolutional codes has been discussed. The paper has shown that usage of such principle allows significantly approximating an area of the decoder effective...
In this paper, as a basic study for combination of turbo equalizer and 4D-8PSK-TCM (4 Dimensional 8 Phase Shift Keying Trellis Coded Modulation) system, which is recommended for X-band band satellite communication in CCSDS, a system combining 8PSK-TCM system and turbo equalizer has been designed and performance evaluation of the system has been performed. BER performance of 8PSK and 8PSK-TCM systems...
In order to address a wide variety of future requirements, Generalized Frequency Division Multiplexing (GFDM), a non-orthogonal multicarrier scheme, is considered as one of the most promising techniques available today. To improve the orthogonality of the conventional GFDM system, a multi-taper implementation of GFDM (MGFDM) using discrete prolate spheroidal sequences (DPSSs) or multi-tapers, which...
We present a deep convolutional decoder architecture that can generate volumetric 3D outputs in a compute- and memory-efficient manner by using an octree representation. The network learns to predict both the structure of the octree, and the occupancy values of individual cells. This makes it a particularly valuable technique for generating 3D shapes. In contrast to standard decoders acting on regular...
Convolutive Non-Negative Matrix Factorization model factorizes a given audio spectrogram using frequency templates with a temporal dimension. In this paper, we present a convolutional auto-encoder model that acts as a neural network alternative to convolutive NMF. Using the modeling flexibility granted by neural networks, we also explore the idea of using a Recurrent Neural Network in the encoder...
In this paper we propose a model for the generation of error patterns at the output of a turbo decoder. One of the advantages of this model is that it can be used to generate the error sequence with little effort. Thus, it provides a basis for designing hybrid concatenated codes (HCCs) employing the turbo code as inner code. These coding schemes combine the features of parallel and serially concatenated...
In this paper, we propose a chaotic convolutional encryption scheme based on multiple chaos mapping. The scheme employs the characteristics of pseudo randomness and sensitivity to initial conditions of chaos mapping. It generates time-varying state transition matrix through modulo-two adder between multiple chaos sequences and input data as well as the state values of status registers in convolutional...
Lossy image compression methods always introduce various unpleasant artifacts into the compressed results, especially at low bit-rates. In recent years, many effective soft decoding methods for JPEG compressed images have been proposed. However, to the best of our knowledge, very few works have been done on soft decoding of JPEG 2000 compressed images. Inspired by the outstanding performance of Convolution...
This paper presents a set of full-resolution lossy image compression methods based on neural networks. Each of the architectures we describe can provide variable compression rates during deployment without requiring retraining of the network: each network need only be trained once. All of our architectures consist of a recurrent neural network (RNN)-based encoder and decoder, a binarizer, and a neural...
Most of the conventional face hallucination methods assume the input image is sufficiently large and aligned, and all require the input image to be noise-free. Their performance degrades drastically if the input image is tiny, unaligned, and contaminated by noise. In this paper, we introduce a novel transformative discriminative autoencoder to 8X super-resolve unaligned noisy and tiny (16X16) low-resolution...
Text instance as one category of self-described objects provides valuable information for understanding and describing cluttered scenes. In this paper, we explore the task of unambiguous text localization and retrieval, to accurately localize a specific targeted text instance in a cluttered image given a natural language description that refers to it. To address this issue, first a novel recurrent...
As the mobile radio communication needs of uniformed and emergency services soared, two way land mobile radio communication systems are evolved from analog to digital. Although digital radios have better communication range, noise performance and provide superior voice quality in most cases compared to analog counterparts, they have hard time to maintain good voice quality in particular conditions...
We demonstrate an alternative approach to 25Gbps 2D TCM PAM4 for TDM-PON with 10GHz optics, which employs M-algorithm at its decoder. Compared to PAM4, 2D TCM PAM4 brings the power budget up by ∼3dB with low complexity.
The main aspect considered in this paper is a comparison of interleaver sizes for convolutional and low-density parity-check codes (LDPC) employed for 100 Gbps wireless communication at 240 GHz with parallel sequence spread spectrum (PSSS). Interleavers required for PSSS-15 and convolutional codes are larger in silicon area than a complete Reed-Solomon decoder. Thus, convolutional codes are not recommended...
Detecting hand-object interactions is a challenging problem with many applications in the human-computer interaction domain. We present a real-time method that automatically detects hand-object interactions in RGBD sensor data and tracks the object's rigid pose over time. The detection is performed using a fully convolutional neural network, which is purposefully trained to discern the relationship...
Modelling of facial dynamics, as well as recovering of latent dimensions that correspond to facial dynamics is of paramount importance for many tasks relevant to facial behaviour analysis. Currently, analysis of facial dynamics is performed by applying linear techniques, mainly, on sparse facial tracks. In this, paper we propose the first, to the best of our knowledge, methodology for extracting lowdimensional...
The task of the definition of an a priori unknown Error Correcting code is one of the major tasks for governmental radio control authorities. In particular, the case of the choice of the most probable ECC from the predefined ECCs set. The SA-method (Syndromes analysis method) is suggested to solve the issue. This method is based on the sequences syndrome analysis. Here are given basic results, which...
Low-density parity-check convolutional codes (LDPC-CCs) are generally decoded using sliding- window based message passing decoding. Based on the sliding-window decoding, an informed dynamic scheduling (IDS) for LDPC-CC is proposed in this work, where the decoding convergence can be significantly accelerated. Since the number of processors required for a satisfactory performance can be reduced, the...
In this work, the construction of non-recursive nonsystematic convolutional codes that allow to achieve secure transmission over a two-link compound wiretap channel is proposed. The code design goal is that, whenever an eavesdropper has access to one of the two links, he cannot recover any of the transmitted information bits. Secure transmission is achieved by considering a special family of convolutional...
This paper investigates the performance of convolutional codes with quadrature amplitude modulation transmitted over the Bernoulli-Gaussian impulsive noise channel. First, the performance superiority of blanking over clipping of the symbols affected by noise pulses is proved through the computation of a lower bound on the bit error rate. Next, lower and upper bounds on the bit error rate performance...
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