Generalization of Spectral Flatness Measure for Non-Gaussian Linear Processes

Dubnov, Shlomo

doi:10.1109/lsp.2004.831663

Cited by 111 publications

(56 citation statements)

References 4 publications

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“…One of these has been pointed out by Gingras et al (2013): the spectral flatness, a quantitative measure of tonality, has turned out to be valuable in the identification of different clades of frogs. The spectral flatness, also known as tonality coefficient or Wiener entropy, is calculated as the geometric mean of the power spectrum divided by its arithmetric mean (Dubnov 2004). This measurement has not been tested so far as a tool for species delimitation in taxonomic approaches, but similar to dominant frequency, spectral flatness has been found to be inversely related to SVL in three of four frog clades studied (Gingras et al 2013).…”

Section: Dqlgdhmentioning

confidence: 99%

The use of bioacoustics in anuran taxonomy: theory, terminology, methods and recommendations for best practice

Köhler

Jansen

Rodríguez³

et al. 2017

Zootaxa

459

410

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Vocalizations of anuran amphibians have received much attention in studies of behavioral ecology and physiology, but also provide informative characters for identifying and delimiting species. We here review the terminology and variation of frog calls from a perspective of integrative taxonomy, and provide hands-on protocols for recording, analyzing, comparing, interpreting and describing these sounds. Our focus is on advertisement calls, which serve as premating isolation mechanisms and, therefore, convey important taxonomic information. We provide recommendations for terminology of frog vocalizations, with call, note and pulse being the fundamental subunits to be used in descriptions and comparisons. However, due to the complexity and diversity of these signals, an unequivocal application of the terms call and note can be challenging. We therefore provide two coherent concepts that either follow a note-centered approach (defining uninterrupted units of sound as notes, and their entirety as call) or a call-centered approach (defining uninterrupted units as call whenever they are separated by long silent intervals) in terminology. Based on surveys of literature, we show that numerous call traits can be highly variable within and between individuals of one species. Despite idiosyncrasies of species and higher taxa, the duration of calls or notes, pulse rate within notes, and number of pulses per note appear to be more static within individuals and somewhat less affected by temperature. Therefore, these variables might often be preferable as taxonomic characters over call rate or note rate, which are heavily influenced by various factors. Dominant frequency is also comparatively static and only weakly affected by temperature, but depends strongly on body size. As with other taxonomic characters, strong call divergence is typically indicative of species-level differences, whereas call similarities of two populations are no evidence for them being conspecific. Taxonomic conclusions can especially be drawn when the general advertisement call structure of two candidate species is radically different and qualitative call differences are thus observed. On the other hand, quantitative differences in call traits might substantially vary within and among conspecific populations, and require careful evaluation and analysis. We provide guidelines for the taxonomic interpretation of advertisement call differences in sympatric and allopatric situations, and emphasize the need for an integrative use of multiple datasets (bio-acoustics, morphology, genetics), particularly for allopatric scenarios. We show that small-sized frogs often emit calls with frequency components in the ultrasound spectrum, although it is unlikely that these high frequencies are of biological relevance for the majority of them, and we illustrate that detection of upper harmonics depends also on recording distance because higher frequencies are attenuated more strongly. Bioacoustics remains a prime approach in integrative taxonomy of anurans if uncertainty due to possible intraspecific variation and technical artifacts is adequately considered and acknowledged.

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Section: Dqlgdhmentioning

confidence: 99%

The use of bioacoustics in anuran taxonomy: theory, terminology, methods and recommendations for best practice

Köhler

Jansen

Rodríguez³

et al. 2017

Zootaxa

459

410

View full text Add to dashboard Cite

show abstract

“…for a white process. From (16) we can introduce the Spectral Flatness Measure (SFM) [10]: SFM is a well-known accepted method for evaluation of the "whiteness" (or "compressibility" in audio or imaging applications) of a signal. It can be shown that , which also follows from the non-negativity of .…”

Section: Mathematical Definition Of Mirmentioning

confidence: 99%

“…To ensure that the proposed waveforms have Low Probability Intercept (LPI) characteristic, it is necessary to evaluate the Mutual Information Rate (MIR) i.e. the additional information that is added when one more sample is observed [10]. MIR is related to the concepts of joint and conditional entropy of a stochastic process [11].…”

Section: Introductionmentioning

confidence: 99%

Noise radar technology: Pseudorandom waveforms and their information rate

Galati

Pavan

Palo

2014

2014 15th International Radar Symposium (IRS)

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-The well-known LPI (Low Probability of Intercept) and antispoofing capabilities of some radar waveforms as well some other desirable feature such as a low sidelobes level of their autocorrelation function can be enhanced by "tailored" pseudorandom sequences, whose phase is made up by a deterministic part plus a variable random term. With such an approach it is possible to design a virtually unlimited number of noisy waveforms with good auto-correlation properties (PSLR, i.e. Peak to Side Lobe Ratio) and, for MIMO applications, good orthogonality between them. In this paper the LPI characteristic are analyzed by evaluation of the variation of their information rate with their "randomness" varying. It results that an ad-hoc tradeoff between the different requirements (LPI, PSLR) is required in most cases.

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“…Dubnov [17] considers the class of stationary Gaussian processes, for which the entropy rate may be obtained analytically from the power spectral density function S(ω) of the signal, and found that the multi-information rate can be expressed as…”

Section: B Real-valued Signals and Audio Analysismentioning

confidence: 99%

Cognitive music modelling: An information dynamics approach

Abdallah

Ekeus

Foster

et al. 2012

2012 3rd International Workshop on Cognitive Information Processing (CIP)

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Abstract-We describe an information-theoretic approach to the analysis of music and other sequential data, which emphasises the predictive aspects of perception, and the dynamic process of forming and modifying expectations about an unfolding stream of data, characterising these using the tools of information theory: entropies, mutual informations, and related quantities. After reviewing the theoretical foundations, we discuss a few emerging areas of application, including musicological analysis, real-time beat-tracking analysis, and the generation of musical materials as a cognitively-informed compositional aid.

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Generalization of Spectral Flatness Measure for Non-Gaussian Linear Processes

Cited by 111 publications

References 4 publications

The use of bioacoustics in anuran taxonomy: theory, terminology, methods and recommendations for best practice

The use of bioacoustics in anuran taxonomy: theory, terminology, methods and recommendations for best practice

Noise radar technology: Pseudorandom waveforms and their information rate

Cognitive music modelling: An information dynamics approach

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