convolutional code

The scheme is basically a convolutional code of rates (r,r+1).

It uses a convolutional code for error detection and correction.

Convolutional codes work on bit or symbol streams of arbitrary length.

The following definition for a quantum convolutional code utilizes the set in its description.

Fundamentally, convolutional codes do not offer more protection against noise than an equivalent block code.

Two main categories are convolutional codes and block codes.

Trellis diagram in the article about convolutional codes.

In 1955, Elias introduced convolutional codes as an alternative to block codes.

The Viterbi algorithm provided the basis for the main decoding strategy of convolutional codes.

Convolutional codes are implemented as either systematic or non-systematic codes.

The 8-level code used on the prototype systems is a convolutional code, storing about 2.5 bits per data cell.

Convolutional codes are processed on a bit-by-bit basis.

A convolutional code can be turned into a block code, if desired, by "tail-biting".

In practical communication systems, convolutional codes tend to be one of the more widely used channel codes.

Non-systematic convolutional codes can provide better performance under maximum-likelihood (Viterbi) decoding.

A quantum convolutional code admits an equivalent definition in terms of the delay transform or -transform.

The idea behind a convolutional code is to make every codeword symbol be the weighted sum of the various input message symbols.

Channel codes are made up of two main type: convolutional codes and block codes.

Punctured convolutional codes are also called "perforated".

Several algorithms exist for decoding convolutional codes.

The Reed-Solomon code, like the convolutional code, is a transparent code.

Convolutional codes.

The Viterbi algorithm is the optimum algorithm used to decode convolutional codes.

Turbo equalizer: applies turbo decoding while treating the channel as a convolutional code.

Extraction of the hidden signal is not exact but is based on recovering the convolutional codes through statistical cross-correlation.