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  2. Recursive least squares filter - Wikipedia

    en.wikipedia.org/wiki/Recursive_least_squares_filter

    In the forward prediction case, we have () = with the input signal () as the most up to date sample. The backward prediction case is d ( k ) = x ( k − i − 1 ) {\displaystyle d(k)=x(k-i-1)\,\!} , where i is the index of the sample in the past we want to predict, and the input signal x ( k ) {\displaystyle x(k)\,\!} is the most recent sample.

  3. Python (programming language) - Wikipedia

    en.wikipedia.org/wiki/Python_(programming_language)

    Python 3.0, released in 2008, was a major revision not completely backward-compatible with earlier versions. Python 2.7.18, released in 2020, was the last release of Python 2. [37] Python consistently ranks as one of the most popular programming languages, and has gained widespread use in the machine learning community. [38] [39] [40] [41]

  4. RLC circuit - Wikipedia

    en.wikipedia.org/wiki/RLC_circuit

    The tuning application, for instance, is an example of band-pass filtering. The RLC filter is described as a second-order circuit, meaning that any voltage or current in the circuit can be described by a second-order differential equation in circuit analysis. The three circuit elements, R, L and C, can be combined in a number of different ...

  5. Python syntax and semantics - Wikipedia

    en.wikipedia.org/wiki/Python_syntax_and_semantics

    Python sets are very much like mathematical sets, and support operations like set intersection and union. Python also features a frozenset class for immutable sets, see Collection types. Dictionaries (class dict) are mutable mappings tying keys and corresponding values. Python has special syntax to create dictionaries ({key: value})

  6. Neural scaling law - Wikipedia

    en.wikipedia.org/wiki/Neural_scaling_law

    For example, for the same task, one architecture might have = while another might have =. They also found that for a given architecture, the number of parameters necessary to reach lowest levels of loss, given a fixed dataset size, grows like N ∝ D β {\displaystyle N\propto D^{\beta }} for another exponent β {\displaystyle \beta } .

  7. Newton's method - Wikipedia

    en.wikipedia.org/wiki/Newton's_method

    The following is an example of a possible implementation of Newton's method in the Python (version 3.x) programming language for finding a root of a function f which has derivative f_prime. The initial guess will be x 0 = 1 and the function will be f ( x ) = x 2 − 2 so that f ′ ( x ) = 2 x .

  8. List of Python software - Wikipedia

    en.wikipedia.org/wiki/List_of_Python_software

    SageMath is a large mathematical software application which integrates the work of nearly 100 free software projects. SymPy, a symbolic mathematical calculations package; PyMC, python module containing Bayesian statistical models and fitting algorithms, including Markov chain Monte Carlo.

  9. Temporal difference learning - Wikipedia

    en.wikipedia.org/wiki/Temporal_difference_learning

    TD-Lambda is a learning algorithm invented by Richard S. Sutton based on earlier work on temporal difference learning by Arthur Samuel. [11] This algorithm was famously applied by Gerald Tesauro to create TD-Gammon, a program that learned to play the game of backgammon at the level of expert human players.