What is he best known for?
The fields of study he is best known for:
- Statistics
- Acoustics
- Artificial intelligence
David M. Green mainly focuses on Statistics, Acoustics, Communication, Psychoacoustics and Speech recognition.
His work on Range as part of general Statistics study is frequently linked to Correlation, therefore connecting diverse disciplines of science.
His Acoustics research is multidisciplinary, incorporating perspectives in Signal transfer function, Transfer function, Center frequency and Microphone.
His work carried out in the field of Psychoacoustics brings together such families of science as Phase noise and Intensity.
His Speech recognition research integrates issues from Psychophysics, Psychometric function, Informational masking, Stimulus and Detection theory.
His Psychophysics research is multidisciplinary, incorporating elements of Psychophysiology and Perceptual decision, Sensory system.
His most cited work include:
- Signal Detection Theory and Psychophysics (9847 citations)
- Sound Localization by Human Listeners (939 citations)
- Frequency discrimination as a function of frequency and sensation level (328 citations)
What are the main themes of his work throughout his whole career to date?
David M. Green focuses on Acoustics, Statistics, Stimulus, Intensity and Profile analysis.
David M. Green has included themes like Amplitude, Waveform, Noise and Masking in his Acoustics study.
His work deals with themes such as Detection theory and Logarithm, which intersect with Amplitude.
His Statistics research is multidisciplinary, relying on both Loudness, Algorithm and Psychometric function.
David M. Green interconnects Speech recognition and Psychophysics in the investigation of issues within Stimulus.
His research on Speech recognition frequently connects to adjacent areas such as Psychoacoustics.
He most often published in these fields:
- Acoustics (42.97%)
- Statistics (25.70%)
- Stimulus (10.04%)
What were the highlights of his more recent work (between 1988-2020)?
- Acoustics (42.97%)
- Statistics (25.70%)
- Spectral shape analysis (9.64%)
In recent papers he was focusing on the following fields of study:
David M. Green spends much of his time researching Acoustics, Statistics, Spectral shape analysis, Stimulus and Psychometric function.
His Acoustics study incorporates themes from Tone, Intensity, Spectral density and Bandwidth.
His research integrates issues of Annoyance, Noise and Econometrics in his study of Statistics.
His Stimulus study combines topics from a wide range of disciplines, such as Speech recognition, Harmonics, Biological system, Psychophysics and Temporal asynchrony.
The study incorporates disciplines such as Stimulus frequency and Communication channel in addition to Psychophysics.
His research in Psychometric function intersects with topics in Estimation theory, Standard error and Standard deviation.
Between 1988 and 2020, his most popular works were:
- Sound Localization by Human Listeners (939 citations)
- A panoramic code for sound location by cortical neurons (320 citations)
- Directional sensitivity of sound‐pressure levels in the human ear canal (190 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Artificial intelligence
- Acoustics
David M. Green mostly deals with Psychometric function, Statistics, Acoustics, Econometrics and Psychophysics.
His Psychometric function research is multidisciplinary, relying on both Stimulus, Sine wave, Audiogram and Standard deviation.
His Stimulus research includes elements of Cognitive psychology, Speech recognition, Intensity discrimination and Signal band.
The various areas that David M. Green examines in his Statistics study include Trial Type and Same different.
His studies deal with areas such as Center frequency, Microphone and Transfer function as well as Acoustics.
His Psychophysics study incorporates themes from Rise time, Harmonics, Communication channel and Backward masking.
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