This paper describes a highly parallel analog signal processing method with three-dimensional (3-D) stacked neural network chip for convolutional and deep neural networks (CNNs and DNNs). The proposed chip has a stacked structure, which enables highly parallel mixed-signal operations like human brains with low power consumption. The product-sum operation using analog circuit in highly parallel calculation with low power supply current, but repeated calculations result in excessive noise (e.g.The offset voltage of the amplifier and 1/f noise, kT/C noise etc.) accumulation and degraded calculation accuracy. Therefore, analog signal processing with 3-D stacked multiple layers neural network chip require the noise reduction technique. In this design, correlated double sampling (CDS) is used to noise reduction technique with which reduce noise generated in the circuit. The proposed CDS circuit is designed with CMOS 0.18nm technology. As results of simulation analysis, it was confirmed that the CDS circuit reduced the offset voltage of composing amplifier and the noise voltages of the circuits placed before the CDS circuit to less than 1.25mV.