Reliable adaptive modulation using long-range prediction at a different carrier frequency

2003 ◽  
Author(s):  
Tung-Sheng Yang ◽  
A. Duel-Hallen ◽  
H. Hallen
Keyword(s):  
Long Range ◽  
Carrier Frequency ◽  
Adaptive Modulation ◽  
Long Range Prediction

scholarly journals Sound Design for Vocalizations: Quality in the Woods, Consistency in the Fields

The Condor ◽  
2000 ◽  
Vol 102 (1) ◽  
pp. 81-92 ◽  
Author(s):  
Timothy J. Brown ◽  
Paul Handford
Keyword(s):  
Long Range ◽  
Amplitude Modulation ◽  
Carrier Frequency ◽  
Sound Design ◽  
Habitat Types ◽  
Acoustic Adaptation ◽  
Acoustic Adaptation Hypothesis ◽  
Closed Habitat ◽  
Long Range Communication ◽  
Low Rate

AbstractThe acoustic adaptation hypothesis (AAH) predicts that vocalizations intended for unambiguous long range communication should possess amplitude modulation (AM) characteristics such that the temporal patterning of amplitude degrades less than alternative patterns during transmission through native habitat. The specific predictions are that open habitat signals should be structured as rapid AM trills, whereas closed habitat signals should be structured as low-rate AM tonal whistles. To investigate the benefit of trill- and whistle-structured signals in open and closed habitats, respectively, a high and low carrier frequency set of four synthetic signals which ranged from rapid AM trills to low rate AM whistles were transmitted 3 hours after sunrise through five different habitat types ranging from closed mature forest to open grassland. Results indicate that, on average, whistles degrade less than trills in both habitats. Trills benefit in open habitats through their tendency to be received with a more consistent quality than whistles. Such differences in transmission consistency among AM patterns are not found in closed habitats. While not degrading less on average, lower frequency signals are received with a more consistent quality than are higher frequency signals of the same AM structure, in both open and closed habitats.

Long-range prediction for poorly-known systems

1995 ◽  
Vol 62 (1) ◽  
pp. 227-238 ◽  
Author(s):  
BENEDIKT SCHENKER ◽  
MUKUL AGARWAL
Keyword(s):  
Long Range ◽  
Long Range Prediction
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