Index mapping is a computer science term (also known as a "trivial hash function"[1]) that is used to describe the mapping of raw data, used directly as in array index, for an array.
Mapping
The homebase is used to give the robot at least one point of reference. As Cye runs, he slowly looses accuracy in his positioning. Luckily, Cye knows this and tells the computer just how inaccurate he thinks he is.
Mapping. See Knowledge Mapping or Social Network Mapping.
Message Board. An area on a website where messages can be exchanged and viewed by a workgroup or community. Sometimes referred to as a bulletin board.
mapping function in Lisp, a function that applies a specified function to each element of a list.
matching problem the problem of determining what parts of a program's knowledge are relevant to a given task or real-world situation.
mapping a graph
Mapping techniques which can formalise the knowledge of the objects in a domain and how to reason in that domain in order to support automated inferencing.
Neural Networks ...
Mapping Great Debates: Can Computers Think? From MacroVU, Inc. "A set of 7 poster-sized argumentation maps that chart the entire history of the debate.
The mapping of a port number to an IP Address.
Subnet
A phyiscal network defined within an IP address.
The "mapping" of a conceptual space involves the representation, whether at conscious or unconscious levels, of its structural features.
This mapping is defined by the Kernel:
Feature Space: Transforming the data into feature space makes it possible to define a similarity measure on the basis of the dot product.
When mapping the data in the database to the inputs of the model, there are two types of mapping that can take place: direct and offset.
4.1 Direct Mapping ...
Then a mapping between their values xit and the values of the time series yt (y is the to-be explained variable) is done, so that pairs {xit , yt} are formed.
Predictive Mapping. One application of multiple correspondence analysis is to perform the equivalent of a Multiple Regression for categorical variables, by adding supplementary columns to a design matrix (see also Burt tables).
Correlation mapping, in which roughly 10^12 nanoscale probes are injected into the cerebrospinal fluid; each takes up residence in a random neuron and monitors its activity.
Function A mapping from one space to another. This is usually understood to be a relationship between numbers. Functions that are computable can be calculated by a universal computer.
Also referred to as a community of interest Content mapping Identifying and organising a high-level description of the meaning contained in a collection of electronic document Corporate amnesia The loss of collective experience, ...
It is especially evident that AI has made great strides in the development and mapping of the materialistic or reductionistic aspects of intelligence.
Google has also developed several desktop applications, including Google Earth, an interactive mapping program powered by satellite and aerial imagery that covers the vast majority of the planet.
This restricts the possible mappings available.
Developments from the simple perceptron: ...
Good question - one surprising thing is that the rTMS apparently targeted *just* the synaesthetic color-grapheme mapping and not the "real" color-grapheme mapping in the experiment.
It has to be noted that the same input-output mapping can be implemented by different neural network architectures. Given a problem in hand, the topology for an ANN is not unique.
Static back-propagation is one kind of backpropagation networks that produces a mapping of a static input to a static output. These networks can solve static classification problems such as optical character recognition (OCR).
This stimulation initiates myelination of the nerve fiber, and also asserts in the brain the existence of the fiber and its mapping into whichever cortical area it is involved with.
Mapping metadata (field names and types) from various input formats into a common format for analysis;
Transforming contents of similar variables into a common format; ...
This makes it easy to reformulate pattern-recognition and learning problems in simple terms---for example, finding the "best" such mapping, etc. Seen in this way, the subject presents a pleasing mathematical simplicity.
In response to this crisis a new kind of robot was created to assist miners in mapping out safe routes in real time. The mapmaker is a small robot called Groundhog.
2 Two Basic Feature-Mapping Models 426
9.3 Self-Organizing Map 428
9.4 Properties of the Feature Map 437
9.5 Computer Experiments I: Disentangling Lattice Dynamics Using SOM 445
9.6 Contextual Maps 447
9.7 Hierarchical Vector Quantization 450
9.
Classical estimation techniques have the characteristic of taking all of the data and mapping the data into a few numbers ("estimates"). This is both a virtue and a vice.
Semantics provides "interpretations" of formal languages, in the strict sense that an interpretation is a mapping of the atomic elements of a language (the simple sentences; or the simple terms, predicates, and operators) into a "domain of ...
The rule matrix is a simple graphical tool for mapping the FL control system rules. It accommodates two input variables and expresses their logical product (AND) as one output response variable.
Reinforcement Learning is about learning a mapping from states to a probability distribution over actions. This is called the policy.
Policy = p(s,a) = probability of taking action a when in state s
S = set of all states (assume finite) ...
Phillips (2000) defined the mean of two real positive numbers, and as a mapping or function of the two numbers into a real positive number . The mapping must satisfy three properties: ...
In practice, NNs are especially useful for mapping problems which are tolerant of some errors and have lots of example data available, but to which hard and fast rules can not easily be applied.
Its expertise was in mapping the structure of complex organic chemicals from data gathered by mass spectrometers. After DENDRAL's rules grew to a certain size, its tangled set of statements became difficult to maintain and expand.
"Constrained Clustering as an Optimization Method" (Rose, Gurewitz, & Fox, IEEE Trans Patt Anal and Mach Intel 15(8), 1993, pp785--794)
"GTM: The Generative Topographic Mapping" ...
Inside, they train weights of "neurons". Neural networks use supervised learning, in which inputs and outputs are known and the goal is to build a representation of a function that will approximate the input to output mapping.
 See also: Neural network, Classification, Percept, Data mining, Distribution
  
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