Sentence examples for memory encoder from inspiring English sources

It is clear that the computational complexity grows exponentially with an increase in channel memory, encoder constraint length and interleaver depth.

It is clear that the computational complexity grows exponentially with an increase in channel memory, encoder constraint length, and modulation alphabet size, and it should be clear that computational complexity for long channel memories and large encoder constraint lengths is too high for feasible implementation.

From these analyses, it is clear that NI-JED is extremely expensive in terms of the number of computations required, even for moderate channel memory lengths, encoder constraint lengths, and interleaver depths.

Before encoding, the convolutional encoder memory is initialized with the last 6 bits of the data block being encoded.

'Preserving' the constraint length (binary equivalent) requires that between M' (SB and MB encoders' memory) and M (MNB encoder's memory) there be the formula: M' = Q × M. As expected, the volume of the calculation for the MNB decoder is significantly higher than for SB and MB.

Good systematic recursive encoding matrices with increasing values of encoder memory sizes for a fixed code rate are listed.

The complexity of the NI-JED without interleaving grows exponentially with an increase in either channel memory length or encoder constraint length, while the complexity of the NI-JED with block interleaving is exponentially related to the channel memory length, encoder constraint length, and the interleaver depth.

Each data block is separately encoded by the binary (171, 133) convolutional encoder with memory m = 6.

A rate R = k/n convolution encoder with memory order m can be realized as a k-input, n-output linear sequential circuit with input memory order m; that is, inputs remain in the encoder for an additional m time units after entering.

A convolution encoder has memory, in the sense that the output symbols depend not only on the input symbols, but also on previous inputs and/or outputs.

The number of super-trellis states for an interleaver depth of D=d n, channel memory length L−1, and encoder constraint length K, is M=2 D(L−1)+(K−1).