Biologically-Inspired Modeling of Filtering Noise in Signal Sound

Sound is one of the media that brings
information to human but it is also distracted by noises
that surround us. Human listens to the noise through the
ear and the brain learns and recognizes the signal
sound. The process to filter the noise is done in the
middle ear, to be precise the cochlea. However, to focus
on a desired resonance from the noises to obtain the
desired signal sound, the process to decide on this signal
sound is made in the brain, and then the brain generates
the result. In addition to that matter, there are certain
processes need to be encountered before the result is
produced such as, learning and recognizing the sound.
As for that reason, this research creates a new idea of
gaining data using signal sound. The main objective of
this research is to develop a process to remove signal
noise using concurrent algorithm. This process is
inspired by the human biological body parts which are;
the human ear as the filtering mechanism, and the
human brain as the processing mechanism. Hence, this
research elaborates the development of signal noise
removal model inspired by the human ear and human
brain