A gray code-to-binary code converter includes multiple parallel-in parallel-out (PIPO) latches, each of the multiple PIPO latches configured to output a parallel output gray code by latching a parallel input gray code in response to a sampling signal, and a parallel-in serial-out (PISO) circuit including a first group of switches, the PISO circuit configured to convert the parallel output gray code, which is latched in the multiple PIPO latches, into a binary code, and sequentially output bits of the binary code in units of bit, from a least significant bit (LSB) of the binary code to a most significant bit (MSB) of the binary code, while changing an arrangement of the first group of switches.

This application discloses a decoding method, a decoding device, and a readable storage medium. The decoding method can perform a simple logic operation on the corresponding specified bits in the first bitstream, and generate the corresponding fourth bitstream accordingly to obtain information before encoding. The logic design of this decoding method is simple, which can reduce the complexity of logic circuit design and improve the reliability of decoding.

This application discloses a decoding method, a decoding device, and a readable storage medium. The decoding method can perform a simple logic operation on the corresponding specified bits in the first bitstream, and generate the corresponding fourth bitstream accordingly to obtain information before encoding. The logic design of this decoding method is simple, which can reduce the complexity of logic circuit design and improve the reliability of decoding.

An electronic device for compressing data includes a compression unit, a search engine, and a compression controller. The search engine includes a first buffer, a second buffer, and a plurality of comparators configured to perform matching between data stored in the first buffer and data stored in the second buffer. The compression controller is configured to determine a structure of the search engine, adjust a connection between the first buffer and the second buffer based on the determined structure and cause the compression unit to perform compression on target data using the search engine.

A data rearrangement system is provided. The system includes a data-encoding device and a data-decoding device. The data-encoding device is configured to receive one or more data streams from one or more end devices. The data-encoding device is configured to generate a data-encoding pattern based on quality of service (QoS) information, scheduling policy, and transmission information of the data streams using a neural network model. The data-encoding device is configured to encode the data streams to generate an encoded data stream with an encoder, according to the data-encoding pattern. The data-encoding device is configured to transmit the data-encoding pattern and the encoded data stream to the data-decoding device. The data-decoding device is configured to restore the data stream according to the data-encoding pattern and the encoded data stream.

A data rearrangement system is provided. The system includes a data-encoding device and a data-decoding device. The data-encoding device is configured to receive one or more data streams from one or more end devices. The data-encoding device is configured to generate a data-encoding pattern based on quality of service (QoS) information, scheduling policy, and transmission information of the data streams using a neural network model. The data-encoding device is configured to encode the data streams to generate an encoded data stream with an encoder, according to the data-encoding pattern. The data-encoding device is configured to transmit the data-encoding pattern and the encoded data stream to the data-decoding device. The data-decoding device is configured to restore the data stream according to the data-encoding pattern and the encoded data stream.