# Design of a Configurable Spike-Encoding Circuit Based on Focal Plane Array
## 1 Introduction  
For decades, researchers have been investigating how the brain interacts with the eyeball, as this is one of the most sophisticated and powerful visual processing systems in existence. The semiconductor industry has made significant progress by utilizing bionics technology as a foundation for semiconductor imaging devices and image processing. Silicon-based focal plane array (FPA) imaging chips extend infrared and ultraviolet bands beyond visible light. By mimicking the brain's neurobiological system, a crucial structure in artificial intelligence was created: the spiking neural network (SNN). Information in SNNs is encoded and transmitted through short pulses. These networks are composed of neurons whose action potential generation is described by mathematically non-differentiable equations that approximate the observed behavior of biological systems. SNNs may consume less energy than earlier versions of neural networks running ondedicated hardware because pulses are only exchanged when input is processed [1]. There are still many issues with encoding methods, network structures, training methods, and hardware implementations that must be resolved before these principles can be utilized. This study focuses on the spike-encoding method and hardware implementation of an FPA. Rate encoding and temporal encoding are the two types of spike-encoding methodologies utilized by artificial SNNs [2]. By determining whether the precise timing and order of pulses are essential to the presentation of the information, it is possible to divide all specialized coding schemes into these two categories. Information is encoded into the instantaneous or average spike generation rate of an individual or group of neurons, resulting in a value describing neuronal activity identical to the activation value of an artificial neuron. In temporal encoding methods, spike timing is used to encode information such as absolute timing relative to a global reference, relative timing among spikes from different neurons, or the sequence of spikes from different neurons. Early studies in biology demonstrated that rate coding is a primary method for transmitting information within the nervous system [3]. However, subsequent research has shown that all sensory organs encode their perceptions into the timing of action potentials. [PERSON] spent years conducting experiments to validate the concept of precise pulse timing as an encoding scheme [4]. It is estimated that the human visual system requires 150 ms to process an object recognition task, which supports the theory that spike encodings in biological nervous systems have temporal properties, as rate encodings are insufficient to explain rapid biological responses [5]. These findings were supported by additional investigations of the visual system [6; 7; 8; 9], auditory system [10], tactile system [11], and olfactory system [12; 13]. In addition, experiments revealed a trade-off between rapid response time after stimulus onset and precision. In biomimicry studies of the human tactile system, for instance, the TTFS code has been shown to reliably transmit information about the direction of fingertip force and the shape of the surface in contact with the fingertip faster than possible rate codes and quickly enough to explain how tactile signals are used in natural manipulations. On the other hand, although it has been demonstrated that temporal codes have greater information capacity, faster reaction times, and quicker transmission speeds, their architectures are more complex, and they lack practical training methods. The rate-based encoding scheme does not rely on the precise timing of each individual peak event but rather takes an average over the duration of the program. Their robustness against fluctuations and noise, as well as their simplicity due to their equivalence to current ANN activation values, persuade us. A single spike-encoding method is commonly used for image processing systems based on SNNs.