Abstract

Mathematical modelling of non-linearity due to charge injection phenomenon with variation in desired characteristics of complementary metal oxide semiconductor (CMOS) image sensor (CIS) and correlated double sampling (CDS) circuits is presented. Existing suppression strategies of charge injection effect for CIS and CDS circuits lack in accuracy because of the absence of knowledge of its effect with variation in major device parameters related to switching transistors viz. width (W), length (L), sense node capacitance (Cpd ) and photon current (I ph). Therefore, variations in these parameters under the effect of charge injection have been experimentally studied. Based on the outcomes, it can be concluded that four-parameter logistic regression symmetrical sigmoid function is the best fit for the non-linearity introduced. Also, the devised mathematical model could be utilised as an activation function to train the biological neurons in CIS centred biomedical applications. A brief illustration of the same has been included for electrical stimulation of retinal cells. Further, the higher values of I ph, Cpd and scaling of switching transistors as W min and L > L min can prove effective in reducing the non-linearity. Contrary to previous studies, the higher value of Cpd utilising the normal photodiode found suitable for charge injection suppression in CIS.

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