D Archana, Deepthi Sri R, Deva Dharani P et al. · 2024
The document discusses the development of a mobile application software for small, wireless computing devices, emphasizing the importance of a clear strategy for app success. It introduces Interpretable AI to elucidate prediction results on mobile app success factors and assist developers. An Ensemble Machine Learning Algorithm is used, along with Explainable AI models like LIME and SHAP, achieving a prediction accuracy of 96%.
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Lindy Comstock, Claudia Lainscsek, Vinícius Rezende Carvalho et al. · bioRxiv (Cold Spring Harbor Laboratory) · 2021
State-of-the-art technologies in neural speech decoding utilize data collected from microwires or microarrays implanted directly into the cerebral cortex. Yet as a tool accessible only to individuals with implanted electrodes, speech decoding from devices of this nature is severely limited in its implementation, and cannot be considered a viable solution for widespread application. Speech decoding from non-invasive EEG signals can achieve relatively high accuracy (70-80%), but only from very small classification tasks, with more complex tasks typically yielding a limited (20-50%) classification accuracy. We propose a novel combination of technologies in which transcranial magnetic stimulation (TMS) is first applied to augment the neural signals of interest, producing a greater signal-to-noise ratio in the EEG data. Next, delay differential analysis (DDA) – a cutting-edge computational method based on nonlinear dynamics – is implemented to capture the widest range of information available in the neural signal, by incorporating both linear and nonlinear dynamics.
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Zhe Zhou · 2010
Layered Space Time Coding(LSTC) plays an important role in space-time coding.This article briefly introduces its theory and focuses on the decoding method.By comparing the zero-forcing method and the minimum error method and the introduction of Disturbance offset method come to a conclusion of Decoding performance changes.
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Ros Shilawani Binti S Abdul Kadir · 2007
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Melinda Melinda · 2011
Convolutional codes are used extensively in numerous applications in order to achieve reliable data transfer. In this paper, the parameters of Convolutional codes are introduced and used to investigate its applications, characteristics and performance when employed as inner and outer code in decoding method. To evaluate the parameters, four schemes of Convolutional codes: non-systematic-recursive, systematic-recursive, non-systematic-non-recursive and systematic-non-recursive; are applied. In addition, the implementation of BCJR (Bahl, Cocke, Jelinek and Raviv) algorithm is discussed by applying APP-SISO (a posteriori probabilities - Soft Input Soft Output) decoding for Convolutional codes. The proposed scheme employing inner and outer decoding of Convolutional codes are analysed and compared by using EXIT characteristic of Convolutional decoders. The channel capacity measurements for different rates inner Convolutional codes are described by using BPSK modulation over AWGN channel. BER performances of outer decoding of Convolutional codes are observed for different schemes which are described the process of area beneath in the inverted EXIT function. This is essential to obtain better performance of BER plot indeed. The result shows that inner decoding of Convolutional codes is the best performance for the EXIT function, particularly for non-systematic-recursive. However, outer decoding of this code has not good performance due to having quite larger area beneath than inner code.
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Alexander Barg, Andrew McGregor · 2004
An improved bound is proved on the list-decoding radius of a concatenated code relying upon a combination of (soft-decision) algebraic list decoding and generalized minimum distance (GMD) decoding in the outer level. This bound is further improved if the inner code is a random linear code.
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Manel Abdelhedi, Omessaad Hamdi, Ammar Bouallègue · International Journal of Communications Network and System Sciences · 2010
Low-density parity-check (LDPC) codes are very efficient for communicating reliably through a noisy channel. N.Sourlas [1] showed that LDPC codes, which revolutionize the codes domain and used in many communications standards, can be mapped onto an Ising spin systems. Besides, it has been shown that the Belief-Propagation (BP) algorithm, the LDPC codes decoding algorithm, is equivalent to the Thouless- Anderson-Palmer (TAP) approach [2]. Unfortunately, no study has been made for the other decoding algorithms. In this paper, we develop the Log-Likelihood Ratios-Belief Propagation (LLR-BP) algorithm and its simplifications the BP-Based algorithm and the λ-min algorithm with the TAP approach. We present the performance of these decoding algorithms using statistical physics argument i.e., we present the performance as function of the magnetization.
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Moh. Solehatul Mustofa, Kemal Budi Mulyono, Nurul Fatimah · Cogent Business & Management · 2026
Literature on agribusiness innovation in the Global South still examines product, process, marketing, and organizational innovations as isolated domains, thereby overlooking how their complementarities shape agribusiness performance within resource-constrained and institutionally fragmented socio-technical environments. Addressing this gap, this study advances Configurational Innovation Synergy as a theoretical extension of Innovation Configuration Theory by integrating Dynamic Capabilities to explain how firms orchestrate multi-domain innovations to generate complementarities that enhance performance. Using stratified survey data from 866 Indonesian agribusiness firms across input, production, and marketing sectors, this research models innovation configuration as a higher-order multidimensional construct through PLS-SEM and empirically tests the simultaneous role of explorative–exploitative alignment. The results demonstrate that integrative innovation configurations significantly improve agribusiness performance, with stronger effects when firms balance exploratory and exploitative activities. Theoretically, this study contributes a context-sensitive configurational lens for understanding innovation under Global South constraints; methodologically, it demonstrates the suitability of PLS-SEM for modeling complex higher-order innovation structures; and empirically, it offers large-scale, cross-sector evidence that supports collaborative and frugal innovation practices as pathways for strengthening agribusiness competitiveness in emerging economies.
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LI Ying, WEI Ji-bo · SHILAP Revista de lepidopterología · 2007
A pruning automatic sphere decoding（PASD） algorithm was presented to reduce the complexity and keep the efficiency of ASD simultaneously.The proposed algorithm efficiently reduced the size of the border node list in ASD by statistical pruning,and obtained the tradeoff between the performance of symbol error ratio（SER） and complexity by setting reasonable parameter’s values.Analysis and simulation show that for a higher level（more than 4） modulation,PASD is able to reduce the number of comparisons by at least 30% as compared to ASD without much penalty of the performance in the same SNR region.
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Norbert Görtz · 2000
A new iterative source-channel decoding technique is proposed, which approximates optimal joint source-channel decoding for the channel-encoded quantizer indices of various source signals, that are transmitted in parallel. The algorithm is realized by two types of soft-in/soft-out decoders, which alternately utilize the channel-code and the source-code redundancies to compute and interchange extrinsic information on the databits within several iterations. After the last iteration the output signals of the receiver are computed by meansquare estimators, which exploit the approximately determined a-posteriori probabilities of the quantizer indices.
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2020
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V.K. Bhargava · Proceedings of the IEEE · 1983
Performance of soft decoded extremal self-dual codes of lengths 8 to 72 are obtained over the Gaussian channel. The results indicate that for decoded bit-error rates below 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-3</sup> , which is the main region of interest for coding application, substantial coding gains can be obtained by using extremal self-dual codes.
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Lav R. Varshney · arXiv (Cornell University) · 2008
Departing from traditional communication theory where decoding algorithms are assumed to perform without error, a system where noise perturbs both computational devices and communication channels is considered here. This paper studies limits in processing noisy signals with noisy circuits by investigating the effect of noise on standard iterative decoders for low-density parity-check codes. Concentration of decoding performance around its average is shown to hold when noise is introduced into message-passing and local computation. Density evolution equations for simple faulty iterative decoders are derived. In one model, computing nonlinear estimation thresholds shows that performance degrades smoothly as decoder noise increases, but arbitrarily small probability of error is not achievable. Probability of error may be driven to zero in another system model; the decoding threshold again decreases smoothly with decoder noise. As an application of the methods developed, an achievability result for reliable memory systems constructed from unreliable components is provided.
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Li Wan, Wenyi Zhang · 2024
Guessing random additive noise decoding (GRAND) is a recently proposed decoding paradigm particularly suitable for codes with short length and high rate. Among its variants, ordered reliability bits GRAND (ORBGRAND) exploits soft information in a simple and effective fashion to schedule its queries, thereby allowing efficient hardware implementation. Compared with maximum likelihood (ML) decoding, however, ORBGRAND still exhibits noticeable performance loss in terms of block error rate (BLER). In order to improve the performance of ORBGRAND while still retaining its amenability to hardware implementation, a new variant of ORBGRAND termed RS-ORBGRAND is proposed, whose basic idea is to reshuffle the queries of ORBGRAND so that the expected number of queries is minimized. Numerical simulations show that RS-ORBGRAND leads to noticeable gains compared with ORBGRAND and its existing variants, and is only 0.1dB away from ML decoding, for BLER as low as 10<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-6</sup>.
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Ruben Xavier Rodrigues Teixeira · Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT) · 2025
This study aims to decode the factors that affect the performance of innovation ecosystems. By understanding how these factors influence innovation ecosystems, it is possible to determine what policies are needed to improve the performance of these ecosystems. Considering aggregate data from 100 countries, there are regional and sectoral variations that condition the reading and economic interpretation of the results on the performance of innovation ecosystems. The main motivation is to explore how each of the dimensions of analysis (economic and structural conditions; risk conditions; sectors of economic activity; and crisis episodes) affects the performance of innovation ecosystems. The data were divided into two samples: developed countries and developing countries. After analysing the descriptive statistics and performing a battery of specification tests, we opted to use the Feasible Generalised Least Squares (FGLS) model. The main results reveal that bureaucracy hinders the performance of innovation ecosystems. Furthermore, education is a statistically significant facilitator of the performance of innovation ecosystems. The impacts of corruption control, migration and industry depend on the country's level of development. Furthermore, agriculture has a negative impact, while services have a positive impact. Considering the episodes of crisis, no evidence of significant impacts was found. The results also suggest that public policies should be directed towards promoting digitisation, skills, social integration, corruption control and the social inclusion of skilled migrants.
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Koushik Sil, Manish Agarwal, Dongning Guo et al. · 2007
Abstract — This work studies the performance of multiuser detection and decoding in the downlink of cellular systems based on orthogonal frequency-division multiplexing (OFDM). Of particular interest is a worst case scenario where the desired user is at the cell boundary and subject to an equally strong interferer from a neighboring cell. A flexible iterative Turbo decisionfeedback equalizer (DFE) is proposed and studied numerically, which exhibits good error performance and resilience to fading, requires moderate training and low complexity, and accommodates multiple antennas easily. The scheme performs well without knowledge of the pilots of interfering signals from other cells, which is typically unavailable in practice, while such knowledge may improve the performance significantly. Furthermore, in the absence of knowledge of pilots for the out-of-cell interference, it is found that estimating the filter coefficients of the DFE directly is superior to deriving the coefficients from estimates of the instantaneous channel gains. I.
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Taoufik Majoul, Fathi Raouafi, M. Jaïdane-Saïdane · 2009
Most of results in channel coding theory have been accomplished basing on the additive white Gaussian noise (AWGN) channels assumption. This hypothesis is not fulfilled in realistic environments in communications applications. In this paper, we investigate the robustness of the turbo code decoding algorithm in presence of a generalized Gaussian (GG) noise. This noise model has been proposed for modeling in many applications such as audio and speech processing. The probability density function (PDF) of such model depends on a shape parameter which determines the decay rate of the distribution. This paper presents the decoding performances of turbo code in terms of bit error rate (BER) when the noise PDF departs from Gaussianity into a GG distribution.
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D. Burshtein, G. Miller · 2002
We consider Gallager's (1963) soft decoding (belief propagation) algorithm for decoding low density parity check (LDPC) codes, when applied to an arbitrary binary-input symmetric-output channel. By considering the expected values of the messages, we derive both lower and upper bounds on the performance of the algorithm. We also derive various properties of the decoding algorithm, such as robustness to the initial values of the messages. Our results apply both to regular and irregular LDPC codes.
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Wensheng Sun (4559515), Dennis L. Barbour (4559518) · Figshare · 2017
<p>(A) Population neural response trajectories obtained by projecting the mean spiking rate response across trials onto the first 3 principal components of neural activity. Trajectories are color-coded by sound identity. Neural activities from 30 ms before sound onset to sound offset are plotted. Crosses mark the time points of 30, 50, and 100 ms after sound onset. Arrows denote the direction of trajectory evolution. Visually, trajectories are distinguishable both by the absolute distances between them and by the relative angles between the hyperplanes in which they are embedded. (B-D) Accuracy of decoding sound identity from single trial responses of the neuron population over time. Each panel shows results of decoding with a different method: (B) LDA, (C) TMPEUC, and (D) TMPCOS. Black and blue curves show the results of decoding using 15-ms and 50-ms read-out windows, respectively. Numerical data and analytical results can be found at osf.io/xhmus/. LDA, linear discriminant analysis; PC, principal component; TMPCOS, template matching with angular distance metric; TMPEUC, template matching with Euclidean distance metric.</p>
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Christian Cardinal, David Haccoun, François Gagnon · 2002
A method for analyzing the error performance of the iterative threshold decoder using strict sense multiorthogonal convolutional codes where the multiplicity order is larger or equal to the number of iterations is presented. This allows a tractable analysis, since all random variables are considered independent at each decoding step. The analysis provides a good prediction of the error probability convergence value of the iterative decoding process using strict sense doubly orthogonal convolutional codes.
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