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In recent years, there has been a large push in the U.S. Department of Defense (DoD) to more rapidly respond and adapt to changing technology advancements and emerging threats. Nowhere is an accelerated pace of innovation more needed than in the airborne tactical domain where the predominant communication system, Link 16, has been in use for over 40 years. Airborne tactical systems are often stove-piped,...
This work presents a comparison of two implementations of the last software version of The High Efficiency Video Coding (HEVC) decoder in a single low cost processor ARM Cortex-A series using NEON architecture which is a Single Input Multiple Data (SIMD). By using this technology of optimization, the whole execution time is reduced up to x4. We have analyzed separately all the blocks in the decoder...
Convolutional encoders and Viterbi decoders are the most commonly used channel encoders/decoders used for efficient extraction of message bits. Convolutional encoder used EXOR gates for generating the code bits. Conventional Viterbi decoders use Trellis diagrams for extracting the message bits. Architecture of Viterbi decoder includes Branch Metric Unit (BMU), Path Metric Unit (PMU) and SurvivorMemory...
Signal communication is the method of sending data from one place to another. Signal compression is the technique, used to reduce the amount of data that must be transmitted in the signal communication. Algorithms that produce better compression ratio and less loss of data in the reconstructed signal are needed for signal compression. This paper presents the wavelet based signal compression algorithm...
LDPC block codes (LDPC-BCs) have attracted great interests in recent years by highly parallel computation and good bit-error-rate performance, and one of the decoder implementation issues is high routing complexity. LDPC convolutional codes (LDPC-CCs) not only release routing complexity but also are natural to dynamic length of data frame. Thus, the codes are very suitable for video stream and pre-5G...
We propose a fully automatic method for segmenting myelin and axon from microscopy images of excised mouse spinal cord based on Convolutional Neural Networks (CNNs) and Deep Convolutional Encoder-Decoder. We compare a two-class CNN, multi-class CNN, and multi-class deep convolutional encoder-decoder with traditional methods. The CNN method gives a pixel-wise accuracy of 79.7% whereas an Active Contour...
Distributed video coding is the promising solution for emerging applications such as wireless video surveillance, wireless video sensor networks that have not been supported by traditional video coding standards. Success of distributed video coding is based on exploiting the source statistics at the decoder with availability of some side information. The better the quality of side information, the...
Check node processing dominates the complexity of nonbinary LDPC decoding. Trellis based min-max algorithm[1] can reduce the computation complexity and generate the message from check node to variable node in parallel. In this paper, power representation is used to implement check node processor, adder structures over GF(q) using power representation in trellis based check node processing are proposed...
Statistical error compensation techniques in computing circuits are becoming prevalent, especially as implemented on nanoscale physical substrates. One such technique that has been developed and deployed is algorithmic noise tolerance (ANT), which aggregates information from several computational branches operating at different points along energy-reliability circuit tradeoffs. To understand this...
With the development of flash technology, multilevel per cell (MLC) NAND flash memory has mastered the key market because of its storage capacity superiority. However, excessive density increment leads to decay of reliability of MLC NAND flash memory, thus an appropriate error correction code (ECC) is required to address this issue. This paper presents an efficient multi-strategy ECC scheme called...
Although High Dynamic Range (HDR) content can provide an enhanced immersive experience for end-users, the impact of channel errors on its perception is unclear due to the lack of a standardized HDR video distribution framework. This paper presents an assessment of the robustness of the two main HDR video distribution architectures, the single-layer 10-bit scheme and the two-layer 8-bit backward-compatible...
Deep learning algorithms modelled with deep architectures have demonstrated impressive results to alleviate common problems of Feedforward Neural Networks, i.e. escaping poor solutions of local minima. Basic architecture concepts behind these powerful models have been set up by preliminary research on Neural Networks, including the application of unsupervised pretraining algorithms and greedy layer-wise...
Security places an important role in communication applications for secure data transfers. Image Steganography is one of the most reliable technique in encryption and decryption of an image (hidden) inside other image (cover) such way that only cover image is visible. In this paper frequency domain Image Steganography using DWT and Modified LSB technique is proposed. The proposed approach uses DWT...
Presenting large formal instruction set models as executable functions makes them accessible to engineers and useful for less formal purposes such as simulation. However, it is more difficult to extract information about the behaviour of individual instructions for reasoning. We present a method which combines symbolic evaluation and symbolic execution techniques to provide a rule-based view of instruction...
In this paper, a hardware-efficient folded SC polar decoder based on k-segment decomposition is first proposed. The proposed k-segment scheme employs (k – 1) N1/k-bit decoders to implement the original N-bit decoder, and reduces the number of mixed-nodes from (N – 1) to (k ă 1)( N1/k – 1) with slightly increased latency. In addition, pipelining technique, partial parallel processing, and pre-computation...
Associative Memories (AM) are storage devices that allow addressing content from part of it, in opposition of classical index-based memories. This property makes them promising candidates for various search challenges including pattern detection in images. Clustered based Neural Networks (CbNN) allow efficient design of AM by providing fast pattern retrieval, especially when implemented in hardware...
Turbo codes are well known error-correcting codes used in many communication standards. However, they suffer from error floors. Recently, a method - denoted as the flip and check algorithm - that lowers the error floor of turbo codes was proposed. This method relies on the identification of the least reliable bits during the turbo decoding process. Gains of about one order of magnitude were reached...
Recurrent neural networks that can be trained end-to-end on sequence learning tasks provide promising benefits over traditional recognition systems. In this paper, we demonstrate the application of an attention-based long short-term memory decoder network for offline handwriting recognition and analyze the segmentation, classification and decoding errors produced by the model. We further extend the...
Sparse code multiple access (SCMA) is a new kind of multiple access (MA) technology which ranks one of the most promising candidates for 5G wireless because of its outstanding performance. SCMA enjoys stronger overloading tolerance compared with traditional MA technologies. It also takes the advantage of sparse property to achieve lower complexity when using message passing algorithm (MPA). In this...
Sparse code multiple access (SCMA) is a new kind of multiple access (MA) technology which ranks one of the most promising candidates for 5G wireless because of its outstanding performance. SCMA enjoys stronger overloading tolerance compared with traditional MA technologies. It also takes the advantage of sparse property to achieve lower complexity when using message passing algorithm (MPA). In this...
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