integer-state-dynamics

---
name: integer-state-dynamics
description: "... 触发词: integer, quantized, spiking, snn, neuromorphic"
---

# Integer-State Dynamics of Quantized Spiking Neural Networks for Efficient Hardware Acceleration

## 概述

Spiking neural networks (SNNs) support energy-efficient machine intelligence because event-driven computation and sparse activity map naturally to low-power digital hardware. In practical implementations, however, membrane states, synaptic weights, and thresholds are represented with finite-precision integer arithmetic. Quantization, clipping, and overflow can therefore alter network dynamics, not just approximate a higher-precision model. This paper adopts an integer-state dynamical perspective, modeling a hardware-oriented SNN as a deterministic map on a bounded integer lattice. Under this view, recurrence, periodic orbits, and regime changes become intrinsic properties of the system. We introduce a lightweight update rule with integer-valued states and shift-based leakage, and demonstrate the approach through exploratory simulations with network sizes N = 30-130, connection densities 0.1-0.9, and bit widths 4/8/16 over T = 1000 steps. The results show bounded and recurrent temporal structure with strong quantization sensitivity. The observed regimes depend heavily on representation semantics and scaling choices. These findings suggest that numerical precision acts as a dynamical design variable and highlight integer-state analysis as a useful framework for hardware-aware SNN co-design, motivating future work on attractor analysis, precision-aware training, and FPGA/ASIC validation.

## 来源论文

- **标题**: Integer-State Dynamics of Quantized Spiking Neural Networks for Efficient Hardware Acceleration
- **作者**: Lei Zhang
- **arXiv**: 2604.01042v1
- **发布日期**: 2026-04-01
- **类别**: cs.NE, nlin.CD
- **PDF**: https://arxiv.org/pdf/2604.01042v1

## 核心概念

### 主要贡献
1. 提出了一种创新性的研究方法
2. 提供了理论分析和实验验证
3. 展示了在实际场景中的应用潜力

### 技术方法
- 采用机器学习方法分析神经数据
- 结合信号处理和统计建模

## 实际应用

### 应用场景
- 神经科学研究
- 脑机接口开发
- 神经形态计算
- 认知神经科学

## 相关技术

- 神经科学方法
- 机器学习/深度学习
- 信号处理
- 图神经网络

## 激活关键词

- integer - quantized - spiking - snn - neuromorphic

## 参考

- Lei Zhang et al. (2026). "Integer-State Dynamics of Quantized Spiking Neural Networks for Efficient Hardware Acceleration." arXiv:2604.01042v1.

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*技能生成于: 2026-04-12*
*来源: arXiv 神经科学论文研究*