Fast Decoding Research Articles

On improving Tunstall codes

Though many compression methods are based on the use of variable length codes, there has recently been a trend to search for alternatives in which the lengths of the codewords are more restricted, which can have useful applications, such as easier processing and fast decoding. This paper explores the construction of variable-to-fixed length codes, which have been suggested long ago by Tunstall. Using new heuristics based on suffix trees, the performance of Tunstall codes can in some cases be improved by more than 40%.

A Full-Diversity Space-Frequency Codes with Fast Decoding Structure and Optimized Coding Gains

A Full-Diversity Space-Frequency Codes with Fast Decoding Structure and Optimized Coding Gains

Time course of implicit processing and explicit processing of emotional faces and emotional words

Facial expressions are important emotional stimuli during social interactions. Symbolic emotional cues, such as affective words, also convey information regarding emotions that is relevant for social communication. Various studies have demonstrated fast decoding of emotions from words, as was shown for faces, whereas others report a rather delayed decoding of information about emotions from words. Here, we introduced an implicit (color naming) and explicit task (emotion judgment) with facial expressions and words, both containing information about emotions, to directly compare the time course of emotion processing using event-related potentials (ERP). The data show that only negative faces affected task performance, resulting in increased error rates compared to neutral faces. Presentation of emotional faces resulted in a modulation of the N170, the EPN and the LPP components and these modulations were found during both the explicit and implicit tasks. Emotional words only affected the EPN during the explicit task, but a task-independent effect on the LPP was revealed. Finally, emotional faces modulated source activity in the extrastriate cortex underlying the generation of the N170, EPN and LPP components. Emotional words led to a modulation of source activity corresponding to the EPN and LPP, but they also affected the N170 source on the right hemisphere. These data show that facial expressions affect earlier stages of emotion processing compared to emotional words, but the emotional value of words may have been detected at early stages of emotional processing in the visual cortex, as was indicated by the extrastriate source activity.

Optimization of Fast-Decodable Full-Rate STBC with Non-Vanishing Determinants

Full-rate STBC (space-time block codes) with non-vanishing determinants achieve the optimal diversity-multiplexing tradeoff but incur high decoding complexity. To permit fast decoding, Sezginer, Sari and Biglieri proposed an STBC structure with special QR decomposition characteristics. In this paper, we adopt a simplified form of this fast-decodable code structure and present a new way to optimize the code analytically. We show that the signal constellation topology (such as QAM, APSK, or PSK) has a critical impact on the existence of non-vanishing determinants of the full-rate STBC. In particular, we show for the first time that, in order for APSK-STBC to achieve non-vanishing determinant, an APSK constellation topology with constellation points lying on square grid and ring radius √m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> +n <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> (m,n integers) needs to be used. For signal constellations with vanishing determinants, we present a methodology to analytically optimize the full-rate STBC at specific constellation dimension.

Ternary Bradley-Terry model-based decoding for multi-class classification and its extensions

A multi-class classifier based on the Bradley-Terry model predicts the multi-class label of an input by combining the outputs from multiple binary classifiers, where the combination should be a priori designed as a code word matrix. The code word matrix was originally designed to consist of +1 and −1 codes, and was later extended into deal with ternary code {+1,0,−1}, that is, allowing 0 codes. This extension has seemed to work effectively but, in fact, contains a problem: a binary classifier forcibly categorizes examples with 0 codes into either +1 or −1, but this forcible decision makes the prediction of the multi-class label obscure. In this article, we propose a Boosting algorithm that deals with three categories by allowing a ‘don’t care’ category corresponding to 0 codes, and present a modified decoding method called a ‘ternary’ Bradley-Terry model. In addition, we propose a couple of fast decoding schemes that reduce the heavy computation by the existing Bradley-Terry model-based decoding.

Fast Algebraic Decoding of the (89, 45, 17) Quadratic Residue Code

In this letter, the algebraic decoding algorithm of the (89, 45, 17) binary quadratic residue (QR) code proposed by Truong et al. is modified by using the efficient determination algorithm of the primary unknown syndromes. The correctness of the proposed decoding algorithm is verified by computer simulations and the use of two corollaries. Also, simulation results show that the CPU time of this algorithm is approximately 4 times faster than that of the previously mentioned decoding algorithm at least. Therefore, such a fast decoding algorithm can now be applied to achieve efficiently the reliability-based decoding for the (89, 45, 17) QR code. Finally, the performance of its algebraic soft-decision decoder expressed in terms of the bit-error probability versus E <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">b</sub> /N <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0</sub> is given but not available in the literature.

A Content-based Classified Hierarchical Vector Quantization Algorithm for Volume Compression

An improved volumetric compression algorithm is presented in this paper. Histogram technique is used for analyzing the trait of volume data. The volume data is then partitioned into volume bricks which will be classified into two groups, the blocks with meaningless information as one group(also called empty blocks), and those with meaningful information as the other group(also called object blocks). An efficient hierarchical VQ is applied to compress object blocks while for empty blocks, nothing is saved. Compare with analogous Volume Compression algorithm, experimental results demonstrate the proposed algorithm not only can improve the compression rate significantly on the premise of the good quality of reconstruction image, but also can obtain fast decoding speed.

A video coding technique with BTC-PF method for fast decoding

A video coding technique with BTC-PF method for fast decoding We have presented a video coding system that enables fast decoding and there by caters the need of the real time applications like video on demand, video play back, video retrieval. Proposed methodology relies on a fast motion estimation scheme, hierarchical BTC-PF based redundancy removal technique and finally it uses entropy decoding. As the encoding method is free from transformation and quantization steps, the decoding becomes faster. It also maintains the quality within the acceptable limit and improves bpp.

A Study on the Efficient LT Decoding Scheme using GE Triangularization

Abstract In this paper an efficient LT decoding scheme using GE triangularization is proposed. The proposed algorithm has the desirable performance in terms of both overhead and computational complexity. Belief propagationalgorithm is a fast and simple decoding scheme for LT codes. However, for a small code block length k, it requires a large overhead to decode, and OFG which has a small overhead has a large computational complexity. Simulation results show that the proposed algorithm noticeably reduces the computational complexity by more than 1/5 with respect to that of OFG and also its overhead has a small value about 1∼5%. Key Words : Triangularization, On-the-fly Gaussian Elimination, Belief Propagation, Overhead, Computational complexity. * 정회원, 남서울대학교 정보통신공학과(교신저자)접수일자 2011.10.8, 수정완료 2011.11.16게재확정일자 2011.12.16 Ⅰ. 서 론 최근 erasure 채널을 통해 오류 없이 데이터를 전송하기 위한 FEC 부호로서 LT 부호와 Raptor 부호가 많은 관심을 받고 있다 [1] . BEC(binary erasure channel)는 erasure 채널의 대표적인 형태로 패킷 스위칭을 사용하는 유선 인터넷 망이 대표적인 예이다

Speech recognition lattice-generating algorithm with forward-backward language model

In order to lighten the heavy computational burden of one-pass lattice-generating algorithms for speech recognition,a fast two-pass decoding algorithm was proposed on the basis of the forward-backward language model.The forward and backward language models were applied to the first and second decoding processes separately.Furthermore,some optimization rules were given to reduce the impact of language model mismatch and to avoid its side-effects on recognition results.The experimental results show that this algorithm quickens the decoding process without decreasing the recognition accurate rate.

A Fast Constrained Sphere Decoder for Ill Conditioned Communication Systems

This letter proposes a fast constrained sphere decoder for ill conditioned communications systems that exhibits less complexity than but similar performance to the generalised sphere decoder. The operational principle is based on i) the reduction of the search space by setting the hypersphere initial radius to be equal to the distance to a semidefinite program (SDP) estimate; and ii) the introduction of a heuristic pruning rule to limit the GSD spanning tree. The new algorithm achieves significant reduction in the required computational effort at the expense of a small error penalty for large dimensional systems in low signal to noise ratio (SNR) regimes.

A new code compression method for FOTA

This paper presents a new compression method for compressed Firmware-over-the-air (FOTA) that reconstructs a new compressed version from an old compressed version of firmware stored in NAND flash memory. The compressed FOTA requires a small delta that minimizes the amount of update data and an efficient compression method that provides fast encoding and decoding to achieve fast updating and extraction. A fast dictionary-based compression algorithm for the program code is introduced. With a high compression ratio, our method provides relatively fast encoding and very fast decoding. We demonstrate that the compression time during the update process can be reduced by utilizing the copy information stored in the delta without increasing the size of the delta. We present some experimental results to show the impact of this method in terms of the compression ratio, extraction time and updating time.

The Asymmetric Golden Code for Fast Decoding on Time-Varying Channels

The golden code is a full-rate full-diversity space---time code for the two-input two-output channel with good performance but high decoding complexity. The overlaid Alamouti codes were recently proposed as an alternative; in exchange for a slight performance penalty, they have lower decoding complexity on quasistatic channels with QAM alphabets. However, the complexity advantage of the overlaid codes vanishes for time-varying channels. This paper proposes the asymmetric golden code, a novel full-rate and full-diversity space---time code for the two-input two-output channel that offers reduced-complexity decoding on both quasistatic and time-varying channels.

Fast decoding of natural object categories from intracranial field potentials in monkey's visual cortex

Fast decoding of natural object categories from intracranial field potentials in monkey's visual cortex

Zero coefficient-aware IDCT algorithm for fast video decoding

Ever since many well-known image and video coding standards such as JPEG, MPEG, and H.26x started using DCT as a core process in data compression, the design of the fast inverse discrete cosine transform (IDCT) has been an intensive research topic. Most research has focused on a reduction of the number of operations using the butterfly structure. However, the majority of DCT coefficients is zero after quantization and is therefore redundant for IDCT computation. Therefore, we exploited this DCT coefficients redundancy to propose a zero coefficient-aware IDCT algorithm for fast decoding. The proposed method significantly reduces the number of IDCT operations by adaptively including non-zero coefficients in the calculation and employing a table look-up to eliminate multiplication operations in the IDCT process. The proposed zero coefficient-ware algorithm outperformed other existing fast IDCT algorithms in terms of operational complexity. Moreover, the running time was faster than butterfly based IDCT algorithms implemented in MPEG-4 simple profile decoder by a speedup factor of 1.32 times for the SIF/CIF sequences and up to 2.18 times for the HD sequences.

A Simple Orthogonal Space-Time Coding Scheme for Asynchronous Cooperative Systems for Frequency Selective Fading Channels

In this paper, we propose a simple orthogonal space time transmission scheme for asynchronous cooperative systems. In the proposed scheme, OFDM is implemented at the source node, some very simple operations, namely time reversion and complex conjugation, are implemented at the relay nodes, and a two-step of cyclic prefix (CP) removal is performed at the destination. The CP at the source node is used for combating the frequency selective fading channels and the timing errors. In this scheme, the received signals at the destination node have the orthogonal code structure on each subcarrier and thus it has the fast symbol-wise ML decoding and can achieve full spatial diversity when SNR is large without the requirement of symbol level synchronization. It should be emphasized that since no Add/Remove CP or IFFT/FFT operation is needed at the relay nodes, the relay nodes do not have to know any information about the channels and the timing errors, and the complexity of the relay nodes is very low.

Fast Optimal Decoding of Multiplexed Orthogonal Designs by Conditional Optimization

This paper focuses on conditional optimization as a decoding primitive for high rate space-time codes that are obtained by multiplexing in the spatial and code domains. The approach is a crystallization of the work of Hottinen which applies to space-time codes that are assisted by quasi-orthogonality. It is independent of implementation and is more general in that it can be applied to space-time codes such as the Golden Code and perfect space-time block codes, that are not assisted by quasi-orthogonality, to derive fast decoders with essentially maximum likelihood (ML) performance. The conditions under which conditional optimization leads to reduced complexity ML decoding are captured in terms of the induced channel at the receiver. These conditions are then translated back to the transmission domain leading to codes that are constructed by multiplexing orthogonal designs. The methods are applied to several block space-time codes obtained by multiplexing Alamouti blocks where it leads to ML decoding with complexity O(N 2) where N is the size of the underlying QAM signal constellation. A new code is presented that tests commonly accepted design principles and for which decoding by conditional optimization is both fast and ML. The two design principles for perfect space-time codes are nonvanishing determinant of pairwise differences and cubic shaping, and it is cubic shaping that restricts the possible multiplexing structures. The new code shows that it is possible to give up on cubic shaping without compromising code performance or decoding complexity.

SPC: Fast and Efficient Scalable Predictive Coding of Animated Meshes

Abstract Animated meshes are often represented by a sequence of static meshes with constant connectivity. Due to their frame‐based representation they usually occupy a vast amount of bandwidth or disk space. We present a fast and efficient scalable predictive coding (SPC) scheme for frame‐based representations of animated meshes. SPC decomposes animated meshes in spatial and temporal layers which are efficiently encoded in one pass through the animation. Coding is performed in a streamable and scalable fashion. Dependencies between neighbouring spatial and temporal layers are predictively exploited using the already encoded spatio‐temporal neighbourhood. Prediction is performed in the space of rotation‐invariant coordinates compensating local rigid motion. SPC supports spatial and temporal scalability, and it enables efficient compression as well as fast encoding and decoding. Parts of SPC were adopted in the MPEG‐4 FAMC standard. However, SPC significantly outperforms the streaming mode of FAMC with coding gains of over 33%, while in comparison to the scalable FAMC, SPC achieves coding gains of up to 15%. SPC has the additional advantage over FAMC of achieving real‐time encoding and decoding rates while having only low memory requirements. Compared to some other non‐scalable state‐of‐the‐art approaches, SPC shows superior compression performance with gains of over 16% in bit‐rate.

Fast maximum-likelihood decoding of the golden code

Because each golden code codeword conveys four information symbols from an M-ary QAM alphabet, the complexity of an exhaustive-search decoder is proportional to M4. In this paper we prove that the golden code is fast-decodable, meaning that maximum-likelihood decoding is possible with a worst-case complexity proportional to only M2.5. The golden code retains its fast-decodable property regardless of whether the channel varies with time. We also present an efficient implementation of a fast maximum-likelihood decoder that exhibits a low average complexity.

Scaled zero coefficient-aware IDCT algorithm for fast video decoding

Proposed is a scaled zero coefficient-aware fast inverse discrete cosine transform (IDCT) algorithm that substantially outperforms the existing fixed-point 8×8 IDCT standard. The concept of the fixed-point approximation with accurate dyadic terms is applied to the zero coefficient-aware IDCT algorithm, improving the computational complexity of the authors' previous work. The experimental results show that the running time of the proposed scaled zero coefficient-ware algorithm is faster than that of the fixed-point 8×8 IDCT standard by a speed-up factor of 2.0 times on average and up to 2.6 times for the HD sequences.