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  2. 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})

  3. Eye pattern - Wikipedia

    en.wikipedia.org/wiki/Eye_pattern

    The first step of computing an eye pattern is normally to obtain the waveform being analyzed in a quantized form. This may be done by measuring an actual electrical system with an oscilloscope of sufficient bandwidth, or by creating synthetic data with a circuit simulator in order to evaluate the signal integrity of a proposed design.

  4. Graph Fourier transform - Wikipedia

    en.wikipedia.org/wiki/Graph_Fourier_transform

    The definition of convolution between two functions and cannot be directly applied to graph signals, because the signal translation is not defined in the context of graphs. [4] However, by replacing the complex exponential shift in classical Fourier transform with the graph Laplacian eigenvectors, convolution of two graph signals can be defined ...

  5. Barker code - Wikipedia

    en.wikipedia.org/wiki/Barker_code

    “The problem of communication was primarily viewed as a deterministic signal-reconstruction problem: how to transform a received signal, distorted by the physical medium, to reconstruct the original as accurately as possible” [2] or see original. [3] In 1948 electronics was advancing fast but the problem of receiving accurate data had not.

  6. Gabor transform - Wikipedia

    en.wikipedia.org/wiki/Gabor_transform

    When processing temporal signals, data from the future cannot be accessed, which leads to problems if attempting to use Gabor functions for processing real-time signals. A time-causal analogue of the Gabor filter has been developed in [ 2 ] based on replacing the Gaussian kernel in the Gabor function with a time-causal and time-recursive kernel ...

  7. Sparse dictionary learning - Wikipedia

    en.wikipedia.org/wiki/Sparse_dictionary_learning

    The dictionary learning framework, namely the linear decomposition of an input signal using a few basis elements learned from data itself, has led to state-of-art [citation needed] results in various image and video processing tasks. This technique can be applied to classification problems in a way that if we have built specific dictionaries ...

  8. Sub-band coding - Wikipedia

    en.wikipedia.org/wiki/Sub-band_coding

    Sub-band coding and decoding signal flow diagram. In signal processing, sub-band coding (SBC) is any form of transform coding that breaks a signal into a number of different frequency bands, typically by using a fast Fourier transform, and encodes each one independently. This decomposition is often the first step in data compression for audio ...

  9. Non-return-to-zero - Wikipedia

    en.wikipedia.org/wiki/Non-return-to-zero

    The binary signal is encoded using rectangular pulse-amplitude modulation with polar NRZ(L), or polar non-return-to-zero-level code. In telecommunications, a non-return-to-zero (NRZ) line code is a binary code in which ones are represented by one significant condition, usually a positive voltage, while zeros are represented by some other significant condition, usually a negative voltage, with ...