Multichannel active noise control (MCANC) is widely recognized as an effective and efficient solution for acoustic noise and vibration cancellation, such as in high-dimensional ventilation ducts, open windows, and mechanical structures. The feedforward multichannel filtered-x least mean square (FFMCFxLMS) algorithm is commonly used to dynamically adjust the transfer function of the multichannel controllers for different noise environments. The computational load incurred by the FFMCFxLMS algorithm, however, increases exponentially with increasing channel count, thus requiring high-end field-programmable gate array (FPGA) processors. Nevertheless, such processors still need specific configurations to cope with soaring computing loads as the channel count increases. To achieve a high-efficiency implementation of the FFMCFxLMS algorithm with floating-point arithmetic, a novel architecture based on multiple-parallel-branch with folding (MPBF) technique is proposed. This architecture parallelizes the branches and reuses the multiplier and adder in each folded branch so that the tradeoff between throughput and the usage of the hardware resources is balanced. The proposed architecture is validated in an experimental setup that implements the FFMCFxLMS algorithm for the MCANC system with 24 reference sensors, 24 secondary sources, and 24 error sensors, at a sampling and throughput rates of 25 kHz and 260 Mb/s, respectively.

中文翻译：

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基于折叠结构的多重并行分支的多通道滤波x最小均方算法的实际实现，用于大规模有源噪声控制

多通道主动噪声控制 (MCANC) 被广泛认为是消除高维通风管道、开窗和机械结构等声学噪声和振动的有效和高效解决方案。前馈多通道滤波 x 最小均方 (FFMCFxLMS) 算法通常用于针对不同的噪声环境动态调整多通道控制器的传递函数。然而，FFMCFxLMS 算法产生的计算负载随着通道数的增加呈指数增长，因此需要高端现场可编程门阵列 (FPGA) 处理器。尽管如此，随着通道数的增加，这些处理器仍然需要特定的配置来应对飙升的计算负载。为了使用浮点算法高效实现 FFMCFxLMS 算法，提出了一种基于多并行折叠分支 (MPBF) 技术的新型架构。这种架构将分支并行化并在每个折叠分支中重用乘法器和加法器，从而平衡吞吐量和硬件资源的使用之间的权衡。所提出的架构在实验设置中得到验证，该实验设置为 MCANC 系统实施 FFMCFxLMS 算法，该系统具有 24 个参考传感器、24 个辅助源和 24 个误差传感器，采样率和吞吐率分别为 25 kHz 和 260 Mb/s。这种架构将分支并行化并在每个折叠分支中重用乘法器和加法器，从而平衡吞吐量和硬件资源的使用之间的权衡。所提出的架构在实验设置中得到验证，该实验设置为 MCANC 系统实施 FFMCFxLMS 算法，该系统具有 24 个参考传感器、24 个辅助源和 24 个误差传感器，采样率和吞吐率分别为 25 kHz 和 260 Mb/s。这种架构将分支并行化并在每个折叠分支中重用乘法器和加法器，从而平衡吞吐量和硬件资源的使用之间的权衡。所提出的架构在实验设置中得到验证，该实验设置为 MCANC 系统实施 FFMCFxLMS 算法，该系统具有 24 个参考传感器、24 个辅助源和 24 个误差传感器，采样率和吞吐率分别为 25 kHz 和 260 Mb/s。