carried out to select various parameter values in the reconstruction process. Performance of DeTER is then evaluated for the simulated data. The second part of validation presents the results and analysis of reconstructions using the Finnish open data and imaging papaya fruits using DoEIT. Initially various parameters are set based on the simulation experiments described.
Setting hyper parameter
The worst-case signal to noise ratio is considered in order to set hyper parameter. The characterization of DoEIT system, reported SNR from 15 dB to 45 dB (Ranade et al
This work focuses on studying signal detection using three different equalization techniques, namely: Zero Forcing (ZF), Minimum Mean Square Error (MMSE) and Beam Forming (BF), for a 4×4 MIMO-system. Results show that ZF equalization is the simplest technique for signal detection, However, Beam Forming (BF) gives better Bit Error Rate (BER) performances at high Signal to Noise Ratio (SNR) values with some complexity in design. For more antennas at the base station, it is too complex to design the weight matrix for ZF, however, it is suitable for BF with the help of good quality digital signal processors. Performance of MIMO-system, with 8 antennas at the base station using BF equalization, is analysed to get BER values at different SNR. Results show a considerable improvement in BER for 8 antennas at the base station.