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Novelty Detection
Novelty detection is the mechanism by which an intelligent organism is able to identify an incoming sensory pattern as being hitherto unknown. If the pattern is sufficiently salient or associated with a high positive or strong negative utility, it will be given computational resources for effective future processing. The principle is long known in neurophysiology, with roots in the orienting response research by E. N. SokolovSokolov, E. N., (1960). Neuronal models and the orienting reflex, In ''The Central Nervous System and Behavior'', Mary A.B. Brazier, ed. NY: JosiahMacy, Jr. Foundation, pp. 187–276 in the 1950s. The reverse phenomenon is habituation, i.e., the phenomenon that known patterns yield a less marked response. Early neural modeling attempts were by Yehuda Salu.Salu, Y. (1988)Models of neural novelty detectors, with similarities to cerebral cortex BioSystems, 21, pp. 99-113, Elsevier. An increasing body of knowledge has been collected concerning the corresponding m ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Data Science
Data science is an interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract or extrapolate knowledge and insights from noisy, structured and unstructured data, and apply knowledge from data across a broad range of application domains. Data science is related to data mining, machine learning, big data, computational statistics and analytics. Data science is a "concept to unify statistics, data analysis, informatics, and their related methods" in order to "understand and analyse actual phenomena" with data. It uses techniques and theories drawn from many fields within the context of mathematics, statistics, computer science, information science, and domain knowledge. However, data science is different from computer science and information science. Turing Award winner Jim Gray imagined data science as a "fourth paradigm" of science (empirical, theoretical, computational, and now data-driven) and asserted that "everything about scien ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Machine Learning
Machine learning (ML) is a field of inquiry devoted to understanding and building methods that 'learn', that is, methods that leverage data to improve performance on some set of tasks. It is seen as a part of artificial intelligence. Machine learning algorithms build a model based on sample data, known as training data, in order to make predictions or decisions without being explicitly programmed to do so. Machine learning algorithms are used in a wide variety of applications, such as in medicine, email filtering, speech recognition, agriculture, and computer vision, where it is difficult or unfeasible to develop conventional algorithms to perform the needed tasks.Hu, J.; Niu, H.; Carrasco, J.; Lennox, B.; Arvin, F.,Voronoi-Based Multi-Robot Autonomous Exploration in Unknown Environments via Deep Reinforcement Learning IEEE Transactions on Vehicular Technology, 2020. A subset of machine learning is closely related to computational statistics, which focuses on making predicti ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Experimental Psychology
Experimental psychology refers to work done by those who apply experimental methods to psychological study and the underlying processes. Experimental psychologists employ human participants and animal subjects to study a great many topics, including (among others) sensation & perception, memory, cognition, learning, motivation, emotion; developmental processes, social psychology, and the neural substrates of all of these. History Early experimental psychology Wilhelm Wundt Experimental psychology emerged as a modern academic discipline in the 19th century when Wilhelm Wundt introduced a mathematical and experimental approach to the field. Wundt founded the first psychology laboratory in Leipzig, Germany. Other experimental psychologists, including Hermann Ebbinghaus and Edward Titchener, included introspection in their experimental methods. Charles Bell Charles Bell was a British physiologist whose main contribution to the medical and scientific communit ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Neurophysiology
Neurophysiology is a branch of physiology and neuroscience that studies nervous system function rather than nervous system architecture. This area aids in the diagnosis and monitoring of neurological diseases. Historically, it has been dominated by electrophysiology—the electrical recording of neural activity ranging from the molar (the electroencephalogram, EEG) to the cellular (intracellular recording of the properties of single neurons), such as patch clamp, voltage clamp, extracellular single-unit recording and recording of local field potentials. However, since the neurone is an electrochemical machine, it is difficult to isolate electrical events from the metabolic and molecular processes that cause them. Thus, neurophysiologists currently utilise tools from chemistry (calcium imaging), physics (functional magnetic resonance imaging, fMRI), and molecular biology (site directed mutations) to examine brain activity. The word originates from the Greek word meaning "nerve" ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Reward System
The reward system (the mesocorticolimbic circuit) is a group of neural structures responsible for incentive salience (i.e., "wanting"; desire or craving for a reward and motivation), associative learning (primarily positive reinforcement and classical conditioning), and positively-valenced emotions, particularly ones involving pleasure as a core component (e.g., joy, euphoria and ecstasy). Reward is the attractive and motivational property of a stimulus that induces appetitive behavior, also known as approach behavior, and consummatory behavior. A rewarding stimulus has been described as "any stimulus, object, event, activity, or situation that has the potential to make us approach and consume it is by definition a reward". In operant conditioning, rewarding stimuli function as positive reinforcers; however, the converse statement also holds true: positive reinforcers are rewarding. The reward system motivates animals to approach stimuli or engage in behaviour that incr ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Outlier
In statistics, an outlier is a data point that differs significantly from other observations. An outlier may be due to a variability in the measurement, an indication of novel data, or it may be the result of experimental error; the latter are sometimes excluded from the data set. An outlier can be an indication of exciting possibility, but can also cause serious problems in statistical analyses. Outliers can occur by chance in any distribution, but they can indicate novel behaviour or structures in the data-set, measurement error, or that the population has a heavy-tailed distribution. In the case of measurement error, one wishes to discard them or use statistics that are robust to outliers, while in the case of heavy-tailed distributions, they indicate that the distribution has high skewness and that one should be very cautious in using tools or intuitions that assume a normal distribution. A frequent cause of outliers is a mixture of two distributions, which may be two ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Change Detection
In statistical analysis, change detection or change point detection tries to identify times when the probability distribution of a stochastic process or time series changes. In general the problem concerns both detecting whether or not a change has occurred, or whether several changes might have occurred, and identifying the times of any such changes. Specific applications, like step detection and edge detection, may be concerned with changes in the mean, variance, correlation, or spectral density of the process. More generally change detection also includes the detection of anomalous behavior: anomaly detection. Introduction A time series measures the progression of one or more quantities over time. For instance, the figure above shows the level of water in the Nile river between 1870 and 1970. Change point detection is concerned with identifying whether, and if so ''when'', the behavior of the series changes significantly. In the Nile river example, the volume of water ch ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Anomaly Detection
In data analysis, anomaly detection (also referred to as outlier detection and sometimes as novelty detection) is generally understood to be the identification of rare items, events or observations which deviate significantly from the majority of the data and do not conform to a well defined notion of normal behaviour. Such examples may arouse suspicions of being generated by a different mechanism, or appear inconsistent with the remainder of that set of data. Anomaly detection finds application in many domains including cyber security, medicine, machine vision, statistics, neuroscience, law enforcement and financial fraud to name only a few. Anomalies were initially searched for clear rejection or omission from the data to aid statistical analysis, for example to compute the mean or standard deviation. They were also removed to better predictions from models such as linear regression, and more recently their removal aids the performance of machine learning algorithms. However, ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Machine Learning
Machine learning (ML) is a field of inquiry devoted to understanding and building methods that 'learn', that is, methods that leverage data to improve performance on some set of tasks. It is seen as a part of artificial intelligence. Machine learning algorithms build a model based on sample data, known as training data, in order to make predictions or decisions without being explicitly programmed to do so. Machine learning algorithms are used in a wide variety of applications, such as in medicine, email filtering, speech recognition, agriculture, and computer vision, where it is difficult or unfeasible to develop conventional algorithms to perform the needed tasks.Hu, J.; Niu, H.; Carrasco, J.; Lennox, B.; Arvin, F.,Voronoi-Based Multi-Robot Autonomous Exploration in Unknown Environments via Deep Reinforcement Learning IEEE Transactions on Vehicular Technology, 2020. A subset of machine learning is closely related to computational statistics, which focuses on making predicti ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Stimulus (physiology)
In physiology, a stimulus is a detectable change in the physical or chemical structure of an organism's internal or external environment. The ability of an organism or organ to detect external stimuli, so that an appropriate reaction can be made, is called sensitivity (excitability). Sensory receptors can receive information from outside the body, as in touch receptors found in the skin or light receptors in the eye, as well as from inside the body, as in chemoreceptors and mechanoreceptors. When a stimulus is detected by a sensory receptor, it can elicit a reflex via stimulus transduction. An internal stimulus is often the first component of a homeostatic control system. External stimuli are capable of producing systemic responses throughout the body, as in the fight-or-flight response. In order for a stimulus to be detected with high probability, its level of strength must exceed the absolute threshold; if a signal does reach threshold, the information is transmitted to t ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Radar Detection
A radar detector is an electronic device used by motorists to detect if their speed is being monitored by police or law enforcement using a radar gun. Most radar detectors are used so the driver can reduce the car's speed before being ticketed for speeding. In general sense, only emitting technologies, like doppler RADAR, or LIDAR can be detected. Visual speed estimating techniques, like ANPR or VASCAR can not be detected in daytime, but technically vulnerable to detection at night, when IR spotlight is used. There are no reports that piezo sensors can be detected. LIDAR devices require an optical-band sensor, although many modern detectors include LIDAR sensors. Most of today's radar detectors detect signals across a variety of wavelength bands: usually X, K, and Ka. In Europe the Ku band is common as well. The past success of radar detectors was based on the fact that radio-wave beams can not be narrow-enough, so the detector usually senses stray and scattered radiat ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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