scholarly journals L(p,q)-labeling of graphs with interval representations

2021 ◽  
Author(s):  
Mehmet Akif Yetim
Keyword(s):  
Interval Representations

Neural Responses in Primary Auditory Cortex Mimic Psychophysical, Across-Frequency-Channel, Gap-Detection Thresholds

2000 ◽  
Vol 84 (3) ◽  
pp. 1453-1463 ◽  
Author(s):  
Jos J. Eggermont
Keyword(s):  
Auditory Cortex ◽  
Cortical Neurons ◽  
Primary Auditory Cortex ◽  
Noise Burst ◽  
Gap Detection ◽  
Frequency Content ◽  
Neural Responses ◽  
Frequency Channel ◽  
Interval Representations ◽  
Onset Response

Responses of single- and multi-units in primary auditory cortex were recorded for gap-in-noise stimuli for different durations of the leading noise burst. Both firing rate and inter-spike interval representations were evaluated. The minimum detectable gap decreased in exponential fashion with the duration of the leading burst to reach an asymptote for durations of 100 ms. Despite the fact that leading and trailing noise bursts had the same frequency content, the dependence on leading burst duration was correlated with psychophysical estimates of across frequency channel (different frequency content of leading and trailing burst) gap thresholds in humans. The duration of the leading burst plus that of the gap was represented in the all-order inter-spike interval histograms for cortical neurons. The recovery functions for cortical neurons could be modeled on basis of fast synaptic depression and after-hyperpolarization produced by the onset response to the leading noise burst. This suggests that the minimum gap representation in the firing pattern of neurons in primary auditory cortex, and minimum gap detection in behavioral tasks is largely determined by properties intrinsic to those, or potentially subcortical, cells.

scholarly journals Irredundancy in multiple interval representations

1987 ◽  
Vol 63 (1) ◽  
pp. 101-108 ◽  
Author(s):  
Edward R. Scheinerman
Keyword(s):  
Interval Representations

scholarly journals Pitch Spelling: A Computational Model

2003 ◽  
Vol 20 (4) ◽  
pp. 411-429 ◽  
Author(s):  
Emilios Cambouropoulos
Keyword(s):  
Computational Model ◽  
Success Rate ◽  
A Priori ◽  
Music Notation ◽  
Optimization Approach ◽  
Interval Optimization ◽  
Piano Sonatas ◽  
Pitch Interval ◽  
Interval Representations ◽  
Spelling Strategies

In this article, cognitive and musicological aspects of pitch and pitch interval representations are explored via computational modeling. The specific task under investigation is pitch spelling, that is, how traditional score notation can be derived from a simple unstructured 12-tone representation (e.g., pitch-class set or MIDI pitch representation). This study provides useful insights both into the domain of pitch perception and into musicological aspects of score notation strategies. A computational model is described that transcribes polyphonic MIDI pitch files into the Western traditional music notation. Input to the proposed algorithm is merely a sequence of MIDI pitch numbers in the order they appear in a MIDI file. No a priori knowledge such as key signature, tonal centers, time signature, chords, or voice separation is required. Output of the algorithm is a sequence of "correctly" spelled pitches. The algorithm is based on an interval optimization approach that takes into account the frequency of occurrence of pitch intervals within the major-minor tonal scale framework. The algorithm was evaluated on 10 complete piano sonatas by Mozart and had a success rate of 98.8% (634 pitches were spelled incorrectly out of a total of 54,418 notes); it was tested additionally on three Chopin waltzes and had a slightly worse success rate. The proposed pitch interval optimization approach is also compared with and tested against other pitch-spelling strategies.

scholarly journals Interval Representations of Cliques and of Subset Intersection Graphs

1989 ◽  
Vol 555 (1 Combinatorial) ◽  
pp. 363-367 ◽  
Author(s):  
EDWARD R. SCHEINERMAN ◽  
DOUGLAS B. WEST
Keyword(s):  
Intersection Graphs ◽  
Interval Representations

Real Interval Representations

2002 ◽  
Vol 46 (2) ◽  
pp. 140-177 ◽  
Author(s):  
Yutaka Nakamura
Keyword(s):  
Real Interval ◽  
Interval Representations

Black-start decision-making with interval representations of uncertain factors

2016 ◽  
Vol 79 ◽  
pp. 34-41 ◽  
Author(s):  
Hong Wang ◽  
Zhenzhi Lin ◽  
Fushuan Wen ◽  
Gerard Ledwich ◽  
Yusheng Xue ◽  
...  
Keyword(s):  
Decision Making ◽  
Interval Representations

scholarly journals Verified Interval Enclosure Techniques for Robust Gain Scheduling Controllers

2020 ◽  
Vol 24 (3) ◽  
pp. 467-491
Author(s):  
Julia Kersten ◽  
Andreas Rauh ◽  
Harald Aschemann
Keyword(s):  
Dynamic Systems ◽  
Blow Up ◽  
Real Life ◽  
Main Idea ◽  
Gain Scheduling ◽  
Linear Matrix ◽  
Worst Case ◽  
Parameters Uncertainty ◽  
Interval Representations ◽  
System States

In real-life applications, dynamic systems are often subject to uncertainty due to model simplifications, measurement inaccuracy or approximation errors which can be mapped to specific parameters. Uncertainty in dynamic systems can come either in stochastic forms or as interval representations, when they are considered as bounded as it will be done in this paper. The main idea, here, is to find a joint approach for an interval-based gain scheduling controller while simultaneously reducing overestimation by enclosing state intervals with the least amount of conservativity. The robust and/ or optimal control design is realized using linear matrix inequalities (LMIs) to find an efficient solution and aims at a guaranteed stabilization of the system dynamics over a predefined time horizon. Since the resulting system is assumed to be asymptotically stable, a temporal reduction of the widths of intervals representing worst-case bounds of the system states at a specific point of time should occur. However, for commonly used approaches in the computation of interval enclosures those interval widths seemingly blow up due to the wrapping effect in many cases. To avoid this, we provide two interval enclosure techniques --- an exploitation of cooperativity and an exponential approach --- and discuss their applicability taking into account two real-life applications, a high-bay rack feeder and an inverse pendulum.

Interval representations, Łukasiewicz implicators and Smets–Magrez axioms

2013 ◽  
Vol 221 ◽  
pp. 192-200 ◽  
Author(s):  
Benjamín Callejas Bedregal ◽  
Regivan Hugo Nunes Santiago
Keyword(s):  
Interval Representations
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