Two‐Click Thresholds in Presence of Band‐Stop Noise
نویسندگان
چکیده
منابع مشابه
Noise Thresholds for Spectral Clustering
Although spectral clustering has enjoyed considerable empirical success in machine learning, its theoretical properties are not yet fully developed. We analyze the performance of a spectral algorithm for hierarchical clustering and show that on a class of hierarchically structured similarity matrices, this algorithm can tolerate noise that grows with the number of data points while still perfec...
متن کاملEffects of background noise on earphone thresholds.
Real-ear attenuation at threshold (REAT) and monaural pure-tone thresholds were determined for normally hearing adults using a supra-aural, Audiocup, and insert earphone. The thresholds were obtained in quiet and in background noises approximating the maximum permissible ambient noise levels (MPANLs) allowed in an audiometric test room specified by ANSI S3.1-1991 and OSHA (1983). The supra-aura...
متن کاملBehavioral measures of signal recognition thresholds in frogs in the presence and absence of chorus-shaped noise.
Anuran amphibians are superb animal models for investigating the mechanisms underlying acoustic signal perception amid high levels of background noise generated by large social aggregations of vocalizing individuals. Yet there are not well-established methods for quantifying a number of key measures of auditory perception in frogs, in part, because frogs are notoriously difficult subjects for t...
متن کاملAcoustic correlated sources direction finding in the presence of unknown spatial correlation noise
In this paper, a new method is proposed for DOA estimation of correlated acoustic signals, in the presence of unknown spatial correlation noise. By generating a matrix from the signal subspace with the Hankel-SVD method, the correlated resource information is extracted from each eigen-vector. Then a joint-diagonalization structure is constructed of the signal subspace and basis it, independent...
متن کاملAn Effective Approach for Robust Metric Learning in the Presence of Label Noise
Many algorithms in machine learning, pattern recognition, and data mining are based on a similarity/distance measure. For example, the kNN classifier and clustering algorithms such as k-means require a similarity/distance function. Also, in Content-Based Information Retrieval (CBIR) systems, we need to rank the retrieved objects based on the similarity to the query. As generic measures such as ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: The Journal of the Acoustical Society of America
سال: 1970
ISSN: 0001-4966
DOI: 10.1121/1.1974824