Shenzhen Synsense Technology Co., Ltd.

Ning Qiao

Hao Liu

Min Wang

Lin Zhang

Weitao Zeng

Saeid Haghighatshoar

LingYun Ke

Jianjun Fan

Zheng Ke

Junjun Yu

Jun Wang

Yudi Ren

Huaqiu Zhang

Kai Zhou

Peng Zhou

Xiwen Gong

Dylan Richard Muir

A divisive normalization method, device, audio feature extractor, and a chip are disclosed. For improving the robustness against variations of the background noise, the proposed per-channel divisive normalization method comprises: obtaining an average number of input spikes over an averaging window by a low-pass filter to produce a threshold parameter, then deciding whether to enable an integrate-and fire (IAF) counter counting over a clock period of a divisive normalization module, when the count value of IAF counter reaches the threshold, resetting IAF counter and producing a single spike at the output. Compared with the prior art, the proposed method does not require any Linear Feedback Shift Register (LFSR) and is easier to implement. It also has a simpler structure, higher accuracy and better statistical performance, and a lower cost and a lower power consumption.

Divisive normalization method, device, audio feature extractor and a chip

A noise filtering device, method, and chip for a dynamic vision sensor (DVS), and an event-driven vision device, and an electronic device are provided. In order to meet multi-dimensional requirements of a denoising solution such as power consumption, delay, storage resources, calculation resources, denoising effect, applicable range of noise types, and hardware implementation difficulty, in this disclosure, global space-domain and time-domain informations are simultaneously aggregated in a shift register, or latest time-domain informations are collected through a space domain, and finally, whether an event generated by a DVS is a noise event is judged on the basis of clustering of space-domain informations and the time-domain informations. While achieving excellent denoising performance, this disclosure has outstanding advantages in the aforementioned multiple dimensions because of advantages of parallel and simple calculation and no dependence on a DVS resolution, etc.

Noise filtering for dynamic vision sensor

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Guangdong, China

Ning Qiao