Search results for "decoding"
showing 10 items of 70 documents
Massively Parallel ANS Decoding on GPUs
2019
In recent years, graphics processors have enabled significant advances in the fields of big data and streamed deep learning. In order to keep control of rapidly growing amounts of data and to achieve sufficient throughput rates, compression features are a key part of many applications including popular deep learning pipelines. However, as most of the respective APIs rely on CPU-based preprocessing for decoding, data decompression frequently becomes a bottleneck in accelerated compute systems. This establishes the need for efficient GPU-based solutions for decompression. Asymmetric numeral systems (ANS) represent a modern approach to entropy coding, combining superior compression results wit…
Improvements in Empathy and Cognitive Flexibility after Court-Mandated Intervention Program in Intimate Partner Violence Perpetrators: The Role of Al…
2016
Research assessing the effectiveness of intervention programs for intimate partner violence (IPV) perpetrators has increased considerably in recent years. However, most of it has been focused on the analysis of psychological domains, neglecting neuropsychological variables and the effects of alcohol consumption on these variables. This study evaluated potential neuropsychological changes (emotional decoding, perspective taking, emotional empathy and cognitive flexibility) and their relationship with alcohol consumption in a mandatory intervention program for IPV perpetrators, as well as how these variables affect the risk of IPV recidivism. The sample was composed of 116 individuals with hi…
Capturing the musical brain with Lasso: Dynamic decoding of musical features from fMRI data.
2013
We investigated neural correlates of musical feature processing with a decoding approach. To this end, we used a method that combines computational extraction of musical features with regularized multiple regression (LASSO). Optimal model parameters were determined by maximizing the decoding accuracy using a leave-one-out cross-validation scheme. The method was applied to functional magnetic resonance imaging (fMRI) data that were collected using a naturalistic paradigm, in which participants' brain responses were recorded while they were continuously listening to pieces of real music. The dependent variables comprised musical feature time series that were computationally extracted from the…
Identifying musical pieces from fMRI data using encoding and decoding models.
2018
AbstractEncoding models can reveal and decode neural representations in the visual and semantic domains. However, a thorough understanding of how distributed information in auditory cortices and temporal evolution of music contribute to model performance is still lacking in the musical domain. We measured fMRI responses during naturalistic music listening and constructed a two-stage approach that first mapped musical features in auditory cortices and then decoded novel musical pieces. We then probed the influence of stimuli duration (number of time points) and spatial extent (number of voxels) on decoding accuracy. Our approach revealed a linear increase in accuracy with duration and a poin…
Acceptability of Intimate Partner Violence among Male Offenders: The Role of Set-Shifting and Emotion Decoding Dysfunctions as Cognitive Risk Factors.
2019
Attitudes towards the acceptability of intimate partner violence against women (IPVAW) contribute to an increased risk of IPVAW perpetration, and these attitudes are common among IPVAW offenders. Research suggests that IPVAW offenders present cognitive deficits related to information processing. Little is known, however, about how these deficits are related to the acceptability of IPVAW. The main aim of this study was to explore the relationship between specific cognitive deficits (i.e., deficits in attention switching, set-shifting, and emotion decoding abilities) and the acceptability of IPVAW in a sample of 84 IPVAW offenders. Results revealed that IPVAW offenders with deficits in attent…
Decoding Musical Training from Dynamic Processing of Musical Features in the Brain
2018
AbstractPattern recognition on neural activations from naturalistic music listening has been successful at predicting neural responses of listeners from musical features, and vice versa. Inter-subject differences in the decoding accuracies have arisen partly from musical training that has widely recognized structural and functional effects on the brain. We propose and evaluate a decoding approach aimed at predicting the musicianship class of an individual listener from dynamic neural processing of musical features. Whole brain functional magnetic resonance imaging (fMRI) data was acquired from musicians and nonmusicians during listening of three musical pieces from different genres. Six mus…
Verso una dimensione narrativa delle mappe
2021
Tra il pensiero e la costruzione dell’architettura il disegno ha un ruolo baricentrico per connettere i diversi protagonisti di una realizzazione e per coinvolgere la collettività facendo percepire inedite prospettive. La scrittura si rivela utile per esplicitare ciò che nella grafica è sotteso e per stabilire un ordine nuovo nel ragionamento progettuale. I rapporti fra segni e significati si moltiplicano nei sistemi informativi recenti in cui si ha la sensazione di poter dire moltissimo (dati numerici e spaziali) ma a volte sfugge quella sintesi indispensabile per una interpretazione concreta, finalizzata alla costruzione di possibili esperienze fisiche. Per l’esplorazione dell’uso di dive…
Design of efficient codes for the AWGN channel based on decomposable binary lattices
1998
This work is concerned with the use of binary decomposable lattice codes over the QAM Gaussian channel. First, we investigate the structure of such class of lattices: we derive consistency conditions for the binary codes appearing in their decomposition and express their nominal coding gain and some bounds for their error coefficient in terms of the parameters of the component codes. Then we describe a general multistage bounded‐distance decoding algorithm with low complexity and we evaluate its performance. Finally, we develop a design example and report the corresponding simulation results; as a reference some comparisons with standard TCM codes are also presented.
Modeling Multi-label Recurrence in Data Streams
2019
Most of the existing data stream algorithms assume a single label as the target variable. However, in many applications, each observation is assigned to several labels with latent dependencies among them, which their target function may change over time. Classification of such non-stationary multi-label streaming data with the consideration of dependencies among labels and potential drifts is a challenging task. The few existing studies mostly cope with drifts implicitly, and all learn models on the original label space, which requires a lot of time and memory. None of them consider recurrent drifts in multi-label streams and particularly drifts and recurrences visible in a latent label spa…
On the Trustworthiness of Error-Correcting Codes
2007
The use of error-correcting codes protects data against accidental or intentional errors, but to what extent can a decoded message be trusted? To answer this question, one has to take the role of the receiver. First, the maximum number of errors Lambda acceptable for decoding is fixed. With the weight distribution, the probability of false decoding can be calculated, conditioned on such a Lambda-bounded strategy. This probability is a monotonously increasing function in the channel error probability p and in the maximum number of accepted errors Lambda. Therefore, pure error detection is more trustworthy than error correction. Moreover, for sufficiently small p, codes with the lexicographic…