This work is a contribution to a drastic change in standard signal processing chains. The main objective is to reduce the power consumption by one or two orders of magnitude. Integrated Smart Devices and Communicating Objects are application domains targeted by this work. In this context, we present a new class of Analog-to-Digital Converters (ADCs), based on an irregular sampling of the analog signal, and an asynchronous design. Because they are not conventional, a complete design methodology is presented. It determines their characteristics given the required effective number of bits and the analog signal properties. it is shown that our approach leads to a significant reduction in terms of hardware complexity and power consumption. A prototype has been designed for speech applications, using the STMicroelectronics 0.18- mu m CMOS technology. Electrical simulations prove that the factor of merit is increased by more than one order of magnitude compared to synchronous Nyquist ADCs
This paper is a contribution to the definition of a new kind of digital signal processing chain. It is focused on Finite-Impulse-Response filtering (FIR) applied to irregularly sampled signals obtained from an asynchronous analog to digital converter. The paper first formalizes the convolution operator in the irregular sampling context. The computational complexity is deduced and compared to the one of standard synchronous FIR filters. It shows that a significant reduction of the computational complexity is achievable, hence a reduction in terms of energy. The paper then describes the architecture of the asynchronous filter. It finally reports the simulations performed on a speech application, resulting in a reduction of the processing power of about one order of magnitude.
This paper is a contribution to the definition of a new kind of digital signal processing chain. It is focused on finite-impulse-response filtering (FIR) applied to irregularly sampled signals obtained from an asynchronous analog to digital converter. The paper first formalizes the convolution operator in the irregular sampling context. The computational complexity is deduced and compared to the one of standard synchronous FIR filters. It shows that a significant reduction of the computational complexity is achievable, hence a reduction in terms of energy. The paper then describes the architecture of the asynchronous filter. It finally reports the simulations performed on a speech application, resulting in a reduction of the processing power of about one order of magnitude
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