Low-Dimensional Signatures of the Sound Production Mechanisms in Subsonic Jets: Towards their Identification and Control

2005 ◽  
Author(s):  
P Jordan ◽  
C. Tinney ◽  
J. Delville ◽  
F. Coiffet ◽  
M. Glauser ◽  
...  
Keyword(s):  
Sound Production ◽  
Low Dimensional ◽  
And Control ◽  
Production Mechanisms

scholarly journals Vocal Creativity in Elephant Sound Production

Biology ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 750
Author(s):  
Angela S. Stoeger ◽  
Anton Baotic ◽  
Gunnar Heilmann
Keyword(s):  
Cognitive Abilities ◽  
Positive Reinforcement ◽  
Sound Production ◽  
Vocal Learning ◽  
Learning Processes ◽  
Fine Tuning ◽  
Social Feedback ◽  
Nasal Tissue ◽  
Production Techniques ◽  
Production Mechanisms

How do elephants achieve their enormous vocal flexibility when communicating, imitating or creating idiosyncratic sounds? The mechanisms that underpin this trait combine motoric abilities with vocal learning processes. We demonstrate the unusual production techniques used by five African savanna elephants to create idiosyncratic sounds, which they learn to produce on cue by positive reinforcement training. The elephants generate these sounds by applying nasal tissue vibration via an ingressive airflow at the trunk tip, or by contracting defined superficial muscles at the trunk base. While the production mechanisms of the individuals performing the same sound categories are similar, they do vary in fine-tuning, revealing that each individual has its own specific sound-producing strategy. This plasticity reflects the creative and cognitive abilities associated with ‘vocal’ learning processes. The fact that these sounds were reinforced and cue-stimulated suggests that social feedback and positive reinforcement can facilitate vocal creativity and vocal learning behavior in elephants. Revealing the mechanism and the capacity for vocal learning and sound creativity is fundamental to understanding the eloquence within the elephants’ communication system. This also helps to understand the evolution of human language and of open-ended vocal systems, which build upon similar cognitive processes.

Low Dimensional Models, Wavelet Transforms and Control

1996 ◽  
pp. 271-331 ◽  
Author(s):  
N. Aubry ◽  
G. Berkooz ◽  
B. Coller ◽  
J. Elezgaray ◽  
P. Holmes ◽  
...  
Keyword(s):  
Wavelet Transforms ◽  
Dimensional Models ◽  
Low Dimensional ◽  
And Control

Transport Properties and Control in Low-Dimensional Quantum Many-Body Systems (abstract)

2009 ◽  
Author(s):  
Lea F. Santos ◽  
Beverly Karplus Hartline ◽  
Renee K. Horton ◽  
Catherine M. Kaicher
Keyword(s):  
Transport Properties ◽  
Many Body ◽  
Many Body Systems ◽  
Low Dimensional ◽  
And Control

Towards Practical Flow Sensing and Control via POD and LSE Based Low-Dimensional Tools (Keynote Paper)

2002 ◽  
Author(s):  
Jeffrey Taylor ◽  
M. N. Glauser
Keyword(s):  
Velocity Field ◽  
Control Strategies ◽  
Adverse Pressure Gradient ◽  
Wall Pressure ◽  
Mean Flow ◽  
Flow Sensing ◽  
Active Feedback ◽  
Low Dimensional ◽  
And Control ◽  
Proper Orthogonal

We present the application of Proper Orthogonal Decomposition (POD) and Linear Stochastic Estimation (LSE) based low-dimensional methods to the flow over a backward facing ramp with an adjustable flap above the ramp which allows for dynamic variation of the adverse pressure gradient. There is a range of flap angles where the flow is incipiently separated so that this relatively simple experiment can be used to flush out ideas for active feedback separation control strategies. The study utilized a combination of PIV and multi-point wall pressure measurements to estimate the full velocity field (mean plus fluctuating) from a modified complementary technique. Specifically we want to identify a low-dimensional mean flow to observe when the profiles are inflectionary, i.e., the incipient condition, just from wall pressure. We demonstrate via this method, that a reasonable estimate of the low dimensional full velocity field can be obtained. This is important for practical active feedback flow control strategies since from wall pressure we can estimate the state of the flow without resorting to probes in the flow.

DETERMINISTIC CHAOS IN SOUNDS OF ASIAN CICADAS

2006 ◽  
Vol 14 (04) ◽  
pp. 555-566 ◽  
Author(s):  
TINA P. BENKO ◽  
MATJAŽ PERC
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Sound Production ◽  
Deterministic Chaos ◽  
Nonlinear Time Series ◽  
Nonlinear Time Series Analysis ◽  
Maximal Lyapunov Exponent ◽  
Sound Recording ◽  
Series Analysis ◽  
Production Mechanisms

We analyze the sound recording of the Southeast Asian cicada Tosena depicta with methods of nonlinear time series analysis. First, we reconstruct the phase space from the sound recording and test it against determinism and stationarity. After positively establishing determinism and stationarity in the series, we calculate the maximal Lyapunov exponent. We find that the latter is positive, from which we conclude that the sound recording possesses clear markers of deterministic chaos. We discuss that methods of nonlinear time series analysis can yield instructive insights and foster the understanding of acoustic and vibrational communication among insects, as well as provide vital clues regarding the origin and functionality of their sound production mechanisms. Furthermore, such studies can serve as means to distinguish different insect genera or even species either from each other or under various environmental influences.

scholarly journals Evidence of sound production by spawning lake trout (Salvelinus namaycush) in lakes Huron and Champlain

2018 ◽  
Vol 75 (3) ◽  
pp. 429-438 ◽  
Author(s):  
Nicholas S. Johnson ◽  
Dennis Higgs ◽  
Thomas R. Binder ◽  
J. Ellen Marsden ◽  
Tyler Buchinger ◽  
...  
Keyword(s):  
Acoustic Telemetry ◽  
Sound Production ◽  
Lake Trout ◽  
Salvelinus Fontinalis ◽  
Salvelinus Namaycush ◽  
Spawning Period ◽  
Sound Recordings ◽  
Laboratory Flume ◽  
And Control

Two sounds associated with spawning lake trout (Salvelinus namaycush) in lakes Huron and Champlain were characterized by comparing sound recordings with behavioral data collected using acoustic telemetry and video. These sounds were named “growls” and “snaps” and were heard on lake trout spawning reefs, but not on a nonspawning reef, and were more common at night than during the day. Growls also occurred more often during the spawning period than the prespawning period, while the trend for snaps was reversed. In a laboratory flume, sounds occurred when male lake trout were displaying spawning behaviors: growls when males were quivering and parallel swimming and snaps when males moved their jaw. Combining our results with the observation of possible sound production by spawning splake (Salvelinus fontinalis × Salvelinus namaycush hybrid) provides rare evidence for spawning-related sound production by a salmonid or any other fish in the superorder Protacanthopterygii. Further characterization of these sounds could be useful for lake trout assessment, restoration, and control.

Towards Sensing and Control of Separation in Subsonic Flows

2003 ◽  
Author(s):  
Monica J. Young ◽  
Mark N. Glauser ◽  
Hiroshi Higuchi ◽  
Jeffrey Taylor
Keyword(s):  
Velocity Field ◽  
Wall Pressure ◽  
Flow State ◽  
Mean Flow ◽  
Airfoil Surface ◽  
Subsonic Flows ◽  
Image Velocimetry ◽  
Low Dimensional ◽  
And Control ◽  
Proper Orthogonal

The purpose of this study is to validate the use of Proper Orthogonal Decomposition POD and Modified Linear Stochastic Estimation mLSE based low-dimensional methods to model an external flow over a NACA 4412 airfoil. By using a combination of Particle Image Velocimetry PIV and multiple airfoil surface pressure measurements, the full velocity field (mean plus fluctuating) is estimated through implementation of a modified complementary technique. We will identify a low-dimensional mean flow just from the wall pressure, specifically observing when the profiles are at the incipient condition. This gives a reasonable estimate of the low-dimensional velocity field. The importance of this work lies in that the flow is estimated from the wall pressure only, providing a practical means for estimating the flow state. This is particularly important for flow control applications.

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