Laguerre-volterra model and architecture for MIMO system identification and output prediction
Laguerre-volterra model and architecture for MIMO system identification and output prediction
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DOI：
10.1109/embc.2014.6944633
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发表时间：
2014-11
期刊：
影响因子：
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通讯作者：
Will X. Y. Li;Yao Xin;Rosa H. M. Chan;D. Song;T. Berger;R. Cheung
中科院分区：
文献类型：
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作者：
Will X. Y. Li;Yao Xin;Rosa H. M. Chan;D. Song;T. Berger;R. Cheung
提出了多输入多输出生物因果系统行为预测的广义数学模型。系统的特性用一组模型参数来表示，这些模型参数可以用随机输入刺激来探测系统。系统根据估计的参数和它的新输入计算预测输出。为该数学模型建立了一个高效的硬件架构，并利用现场可编程门阵列（fpga）实现了其电路。该架构具有可扩展性，其功能已通过使用从实际测量中收集的实验数据进行验证。
A generalized mathematical model is proposed for behaviors prediction of biological causal systems with multiple inputs and multiple outputs (MIMO). The system properties are represented by a set of model parameters, which can be derived with random input stimuli probing it. The system calculates predicted outputs based on the estimated parameters and its novel inputs. An efficient hardware architecture is established for this mathematical model and its circuitry has been implemented using the field-programmable gate arrays (FPGAs). This architecture is scalable and its functionality has been validated by using experimental data gathered from real-world measurement.