Natural language translation device

A method of translating natural language using a Cellular Neural Networks or Cellular Nonlinear Networks (CNN) based integrated circuit, the method comprising:

• receiving, in a natural language translation device having a two-dimensional (2-D) symbol creation module installed thereon, a source sentence in a first natural language to be translated to a target sentence in second natural language one word at a time in sequential order;
• forming, with the 2-D symbol creation module, a multi-layer two-dimensional (2-D) symbol in accordance with a set of 2-D symbol creation rules, the 2-D symbol being a matrix of N×N pixels of K-bit data that contains a super-character, the matrix being divided into M×M sub-matrices with each of the sub-matrices containing (N/M)×(N/M) pixels, said each of the sub-matrices representing one ideogram, the super-character having a characteristic suggesting the i-th word of the target sentence based on the received source sentence, where K, N and M are positive integers or whole numbers, and N is a multiple of M;
• and
• obtaining, with the 2-D symbol creation module, the i-th word of the target sentence by classifying the 2-D symbol via a deep learning model having a plurality of ordered convolution layers in a Cellular Neural Networks or Cellular Nonlinear Networks (CNN) based integrated circuit.