  Due to the evolution of technology and the diffusion of digital television,
many researchers are studying more efficient transmission and reception
methods. This fact occurs because of the demand of transmitting videos with
better quality using new standards such 8K SUPER Hi-VISION. In this scenario,
modulation techniques such as Filter Bank Multi Carrier, associated with
advanced coding and synchronization methods, are being applied, aiming to
achieve the desired data rate to support ultra-high definition videos.
Simultaneously, it is also important to investigate ways of channel estimation
that enable a better reception of the transmitted signal. This task is not
always trivial, depending on the characteristics of the channel. Thus, the use
of artificial intelligence can contribute to estimate the channel frequency
response, from the transmitted pilots. A classical algorithm called
Back-propagation Training can be applied to find the channel equalizer
coefficients, making possible the correct reception of TV signals. Therefore,
this work presents a method of channel estimation that uses neural network
techniques to obtain the channel response in the Brazilian Digital System
Television, called ISDB-TB, using Filter Bank Multi Carrier.
