Search results for "complexity"
showing 10 items of 1094 documents
Color and Timbre Gestures: An Approach with Bicategories and Bigroupoids
2022
White light can be decomposed into different colors, and a complex sound wave can be decomposed into its partials. While the physics behind transverse and longitudinal waves is quite different and several theories have been developed to investigate the complexity of colors and timbres, we can try to model their structural similarities through the language of categories. Then, we consider color mixing and color transition in painting, comparing them with timbre superposition and timbre morphing in orchestration and computer music in light of bicategories and bigroupoids. Colors and timbres can be a probe to investigate some relevant aspects of visual and auditory perception jointly with thei…
Abelian antipowers in infinite words
2019
Abstract An abelian antipower of order k (or simply an abelian k-antipower) is a concatenation of k consecutive words of the same length having pairwise distinct Parikh vectors. This definition generalizes to the abelian setting the notion of a k-antipower, as introduced in Fici et al. (2018) [7] , that is a concatenation of k pairwise distinct words of the same length. We aim to study whether a word contains abelian k-antipowers for arbitrarily large k. S. Holub proved that all paperfolding words contain abelian powers of every order (Holub, 2013 [8] ). We show that they also contain abelian antipowers of every order.
Real-Time Body Gestures Recognition Using Training Set Constrained Reduction
2017
Gesture recognition is an emerging cross-discipline research field, which aims at interpreting human gestures and associating them to a well-defined meaning. It has been used as a mean for supporting human to machine interaction in several applications of robotics, artificial intelligence, and machine learning. In this paper, we propose a system able to recognize human body gestures which implements a constrained training set reduction technique. This allows the system for a real-time execution. The system has been tested on a publicly available dataset of 7,000 gestures, and experimental results have highlighted that at the cost of a little decrease in the maximum achievable recognition ac…
Adaptive distributed outlier detection for WSNs.
2014
The paradigm of pervasive computing is gaining more and more attention nowadays, thanks to the possibility of obtaining precise and continuous monitoring. Ease of deployment and adaptivity are typically implemented by adopting autonomous and cooperative sensory devices; however, for such systems to be of any practical use, reliability and fault tolerance must be guaranteed, for instance by detecting corrupted readings amidst the huge amount of gathered sensory data. This paper proposes an adaptive distributed Bayesian approach for detecting outliers in data collected by a wireless sensor network; our algorithm aims at optimizing classification accuracy, time complexity and communication com…
Multimodal Mean Adaptive Backgrounding for Embedded Real-Time Video Surveillance
2007
Automated video surveillance applications require accurate separation of foreground and background image content. Cost sensitive embedded platforms place realtime performance and efficiency demands on techniques to accomplish this task. In this paper we evaluate pixel-level foreground extraction techniques for a low cost integrated surveillance system. We introduce a new adaptive technique, multimodal mean (MM), which balances accuracy, performance, and efficiency to meet embedded system requirements. Our evaluation compares several pixel-level foreground extraction techniques in terms of their computation and storage requirements, and functional accuracy for three representative video sequ…
Feasibility of Ultra-short Term Complexity Analysis of Heart Rate Variability in Resting State and During Orthostatic Stress
2022
In this work, we study ultra-short term (UST) complexity of Heart Rate Variability (HRV) and its agreement with analysis of standard short-term (ST) HRV recordings obtained at rest and during orthostatic stress. Conditional Entropy (CE) measures have been computed using both a linear Gaussian approximation and a more accurate model-free approach based on nearest neighbors. The agreement between UST and ST indices has been compared via statistical tests and correlation analysis, suggesting the feasibility of exploiting faster algorithms and shorter time series for detecting changes in cardiovascular control during various states.
Prospettive di riforma della tutela penale dell'ambiente nel diritto europeo e sovranazionale
2021
Il saggio descrive le prospettive di riforma della normativa penale ambientale, di recente delineatesi tanto a livello internazionale, quanto in ambito europeo. Pur non spingendosi sino a prevedere i possibili esiti delle dinamiche in corso, il contributo non rinuncia ad analizzarne luci ed ombre, anche alla luce delle difficoltà di tipizzazione delle fattispecie incriminatrici determinata dalla particolare complessità della materia ambientale.
A study of temporal estimation from the perspective of the Mental Clock Model.
2009
M. Cardaci's (2000) Mental Clock Model maintains that a task requiring a low mental workload is associated with an acceleration of perceived time, whereas a task requiring a high mental workload is associated with a deceleration. The authors examined the predictions of this model in a musical listening condition in which musical pieces were audible in several structural complexities. To measure the effects of musical complexity on time estimation, the authors used retrospective and prospective time-estimation paradigms. For the retrospective paradigm, the authors invited participants to listen to a musical piece and then estimate its duration. For the prospective paradigm, the authors invit…
Fast Channel Estimation in the Transformed Spatial Domain for Analog Millimeter Wave Systems
2021
Fast channel estimation in millimeter-wave (mmWave) systems is a fundamental enabler of high-gain beamforming, which boosts coverage and capacity. The channel estimation stage typically involves an initial beam training process where a subset of the possible beam directions at the transmitter and receiver is scanned along a predefined codebook. Unfortunately, the high number of transmit and receive antennas deployed in mmWave systems increase the complexity of the beam selection and channel estimation tasks. In this work, we tackle the channel estimation problem in analog systems from a different perspective than used by previous works. In particular, we propose to move the channel estimati…
Random Feature Approximation for Online Nonlinear Graph Topology Identification
2021
Online topology estimation of graph-connected time series is challenging, especially since the causal dependencies in many real-world networks are nonlinear. In this paper, we propose a kernel-based algorithm for graph topology estimation. The algorithm uses a Fourier-based Random feature approximation to tackle the curse of dimensionality associated with the kernel representations. Exploiting the fact that the real-world networks often exhibit sparse topologies, we propose a group lasso based optimization framework, which is solve using an iterative composite objective mirror descent method, yielding an online algorithm with fixed computational complexity per iteration. The experiments con…