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A linear encoder is a sensor, transducer or readhead paired with a scale that encodes position. The sensor reads the scale in order to convert the encoded position into an analog or digital signal , which can then be decoded into position by a digital readout (DRO) or motion controller.
One encoder-decoder block A Transformer is composed of stacked encoder layers and decoder layers. Like earlier seq2seq models, the original transformer model used an encoder-decoder architecture. The encoder consists of encoding layers that process all the input tokens together one layer after another, while the decoder consists of decoding ...
In general, pseudorandom codes have complex encoders, but pseudorandom codes with the best decoders can have simple encoders. [28] Various constraints are often applied to help ensure that the desired properties expected at the theoretical limit of infinite block size occur at a finite block size. [citation needed]
Autoencoders are often trained with a single-layer encoder and a single-layer decoder, but using many-layered (deep) encoders and decoders offers many advantages. [2] Depth can exponentially reduce the computational cost of representing some functions. Depth can exponentially decrease the amount of training data needed to learn some functions.
The squared norm distance between the received and the actual symbols in the code alphabet may be further simplified into a linear sum/difference form, which makes it less computationally intensive. Consider a 1/2 convolutional code , which generates 2 bits ( 00 , 01 , 10 or 11 ) for every input bit ( 1 or 0 ).
This was initially resolved by changing the original scheme to a BCH-code-like scheme based on a fixed polynomial known to both encoder and decoder, but later, practical decoders based on the original scheme were developed, although slower than the BCH schemes. The result of this is that there are two main types of Reed–Solomon codes: ones ...
Low-density parity-check (LDPC) codes are a class of highly efficient linear block codes made from many single parity check (SPC) codes. They can provide performance very close to the channel capacity (the theoretical maximum) using an iterated soft-decision decoding approach, at linear time complexity in terms of their block length. Practical ...
Encoder–decoder frameworks are based on neural networks that map highly structured input to highly structured output. The approach arose in the context of machine translation , [ 97 ] [ 98 ] [ 99 ] where the input and output are written sentences in two natural languages.
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