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The lookup3 function consumes input in 12 byte (96 bit) chunks. [9] It may be appropriate when speed is more important than simplicity. Note, though, that any speed improvement from the use of this hash is only likely to be useful for large keys, and that the increased complexity may also have speed consequences such as preventing an optimizing compiler from inlining the hash function.
A minimum detectable signal is a signal at the input of a system whose power allows it to be detected over the background electronic noise of the detector system. It can alternately be defined as a signal that produces a signal-to-noise ratio of a given value m at the output.
scikit-learn (formerly scikits.learn and also known as sklearn) is a free and open-source machine learning library for the Python programming language. [3] It features various classification, regression and clustering algorithms including support-vector machines, random forests, gradient boosting, k-means and DBSCAN, and is designed to interoperate with the Python numerical and scientific ...
The MIDAS can also be used for machine learning time series and panel data nowcasting. [6] [7] The machine learning MIDAS regressions involve Legendre polynomials.High-dimensional mixed frequency time series regressions involve certain data structures that once taken into account should improve the performance of unrestricted estimators in small samples.
The fundamental frequency of speech can vary from 40 Hz for low-pitched voices to 600 Hz for high-pitched voices. [12] Autocorrelation methods need at least two pitch periods to detect pitch. This means that in order to detect a fundamental frequency of 40 Hz, at least 50 milliseconds (ms) of the speech signal must be analyzed.
FCC Part 15 mandates at least 50 different channels and at least a 2.5 Hz hop rate for narrow band frequency-hopping systems. GPS satellites broadcast data at a rate of 50 data bits per second – each satellite modulates its data with one PN bit stream at 1.023 million chips per second and the same data with another PN bit stream at 10.23 ...
In particular, Albert Einstein referred to quantum nonlocality as "spooky action at a distance". Software bugs due to action at a distance may arise because a program component is doing something at the wrong time, or affecting something it should not. It is very difficult, however, to track down which component is responsible.
In monitoring and security, an important contribution to alarm detection and alarm verification can be supplied, using sound recognition techniques. In particular, these methods could be helpful for intrusion detection in places like offices, stores, private homes or for the supervision of public premises exposed to person aggression.