Adaptive and MLSE equalizers

`comm.MLSEEqualizer` |
Equalize using maximum likelihood sequence estimation |

CMA Equalizer | Equalize using constant modulus algorithm |

LMS Decision Feedback Equalizer | Equalize using decision feedback equalizer that updates weights with LMS algorithm |

LMS Linear Equalizer | Equalize using linear equalizer that meditorsupdates weights with LMS algorithm |

MLSE Equalizer | Equalize using Viterbi algorithm |

Normalized LMS Decision Feedback Equalizer | Equalize using decision feedback equalizer that updates weights with normalized LMS algorithm |

Normalized LMS Linear Equalizer | Equalize using linear equalizer that updates weights with normalized LMS algorithm |

RLS Decision Feedback Equalizer | Equalize using decision feedback equalizer that updates weights with RLS algorithm |

RLS Linear Equalizer | Equalize using linear equalizer that updates weights using RLS algorithm |

Sign LMS Decision Feedback Equalizer | Equalize using decision feedback equalizer that updates weights with signed LMS algorithm |

Sign LMS Linear Equalizer | Equalize using linear equalizer that updates weights with signed LMS algorithm |

Variable Step LMS Decision Feedback Equalizer | Equalize using decision feedback equalizer that updates weights with variable-step-size LMS algorithm |

Variable Step LMS Linear Equalizer | Equalize using linear equalizer that updates weights with variable-step-size LMS algorithm |

`cma` |
Construct constant modulus algorithm (CMA) object |

`dfe` |
Construct decision-feedback equalizer object |

`equalize` |
Equalize signal using equalizer object |

`lineareq` |
Construct linear equalizer object |

`lms` |
Construct least mean square (LMS) adaptive algorithm object |

`mlseeq` |
Equalize linearly modulated signal using Viterbi algorithm |

`normlms` |
Construct normalized least mean square (LMS) adaptive algorithm object |

`reset (equalizer)` |
Reset equalizer object |

`rls` |
Construct recursive least squares (RLS) adaptive algorithm object |

`signlms` |
Construct signed least mean square (LMS) adaptive algorithm object |

`varlms` |
Construct variable-step-size least mean square (LMS) adaptive algorithm object |

Equalize a BPSK signal using a linear equalizer with an least mean square (LMS) algorithm.

**Compare RLS and LMS Algorithms**

Equalize a QAM signal passed through a frequency-selective fading channel using RLS and LMS algorithms.

This example shows how to a model a communication link with PSK modulation, raised cosine pulse shaping, multipath fading, and adaptive equalization.

This model shows the behavior of adaptive equalizer algorithms at a receiver for modulated data transmitted along a channel.

Equalizing using adaptive or MLSE techniques

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