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  2. Smith predictor - Wikipedia

    en.wikipedia.org/wiki/Smith_predictor

    The Smith predictor (invented by O. J. M. Smith in 1957) is a type of predictive controller designed to control systems with a significant feedback time delay. The idea can be illustrated as follows. Suppose the plant consists of () followed by a pure time delay .

  3. Time delay neural network - Wikipedia

    en.wikipedia.org/wiki/Time_delay_neural_network

    TDNNs can be implemented in virtually all machine-learning frameworks using one-dimensional convolutional neural networks, due to the equivalence of the methods. Matlab: The neural network toolbox has explicit functionality designed to produce a time delay neural network give the step size of time delays and an optional training function. The ...

  4. Types of artificial neural networks - Wikipedia

    en.wikipedia.org/wiki/Types_of_artificial_neural...

    A time delay neural network (TDNN) is a feedforward architecture for sequential data that recognizes features independent of sequence position. In order to achieve time-shift invariance, delays are added to the input so that multiple data points (points in time) are analyzed together. It usually forms part of a larger pattern recognition system.

  5. Domain adaptation - Wikipedia

    en.wikipedia.org/wiki/Domain_Adaptation

    Distinction between usual machine learning setting and transfer learning, and positioning of domain adaptation. Domain adaptation [1] [2] [3] is a field associated with machine learning and transfer learning. This scenario arises when we aim at learning a model from a source data distribution and applying that model on a different (but related ...

  6. Transfer function - Wikipedia

    en.wikipedia.org/wiki/Transfer_function

    The transfer function of a two-port electronic circuit, such as an amplifier, might be a two-dimensional graph of the scalar voltage at the output as a function of the scalar voltage applied to the input; the transfer function of an electromechanical actuator might be the mechanical displacement of the movable arm as a function of electric ...

  7. Statistical learning theory - Wikipedia

    en.wikipedia.org/wiki/Statistical_learning_theory

    This image represents an example of overfitting in machine learning. The red dots represent training set data. The green line represents the true functional relationship, while the blue line shows the learned function, which has been overfitted to the training set data. In machine learning problems, a major problem that arises is that of ...

  8. First-order inductive learner - Wikipedia

    en.wikipedia.org/wiki/First-order_inductive_learner

    Developed in 1990 by Ross Quinlan, [1] FOIL learns function-free Horn clauses, a subset of first-order predicate calculus.Given positive and negative examples of some concept and a set of background-knowledge predicates, FOIL inductively generates a logical concept definition or rule for the concept.

  9. First-order hold - Wikipedia

    en.wikipedia.org/wiki/First-order_hold

    The delayed output makes this a causal system.The impulse response of the delayed FOH does not respond before the input impulse. This kind of delayed piecewise linear reconstruction is physically realizable by implementing a digital filter of gain H(z) = 1 − z −1, applying the output of that digital filter (which is simply x[n]−x[n−1]) to an ideal conventional digital-to-analog ...