The growing demand for deployment of Artificial Intelligence (AI) on resource-constrained edge devices has motivated extensive research on the design of efficient edge-compatible AI hardware accelerators. One of the most promising solutions are the self-adaptive AI accelerators, capable of optimizing in real time their performance and energy consumption according to application requirements. This work introduces the EU-funded project Twinning for Excellence in Adaptive Edge Artificial Intelligence (AIDA4Edge), aimed to advance the state-of-the-art in the design of adaptive neural network accelerators for edge applications. The main goal is to develop a novel hybrid self-adaptive neural network architecture combining spiking and artificial neural networks, and supporting runtime adaptation of network functionality, precision and reliability. Furthermore, we aim to enhance the neural network training by incorporating hardware and quantization constraints in an automated tuning engine.

Abstract Design of optimal and asymptotically optimal quantisation subject to the mean squared error (MSE) criterion is a complex issue, even in the case of uniform scalar quantisation (USQ). The reason is that the MSE distortion dependence on the key designing parameter of USQ for source densities with infinite supports are complex and limit analytical optimisation of USQs. This issue of USQ design has been addressed for some source densities derived from the generalised gamma density. However, to the best of our knowledge, USQ for the one‐sided Rayleigh density has not been studied in detail. This has prompted our research so that this study provides a detailed analysis of USQ for the one‐sided Rayleigh density and proposes an iterative algorithm for its asymptotically optimal design. To estimate signal to quantisation noise ratio, we derive an asymptotic formula having reasonable accuracy for rates higher than 3 bits/sample. Our analysis can be useful in digital‐to‐analogue and analogue‐to‐digital conversion in diversity systems, orthogonal frequency division multiplexing systems and medical image processing.

In this study, a very simple but successful method for designing the pulse‐amplitude modulation (PAM) constellations with non‐equiprobable symbols and not equally spaced amplitudes is presented. The method, inspired by companding quantisation, introduces a constellation design function having a feature that maps the non‐uniformly distributed constellations points into uniform ones. In particular, two classes of piecewise‐linear constellation design function having two segments are provided. In PAM constellation designed by the proposed method, the set of constellation points is divided into two uniform subsets. Each of these subsets is characterised by a certain probability of constellation points and by a constant distance between adjacent points. For this model of PAM constellation, the formulas that enable the elegant assessment of the signal energy and the symbol error probability are derived. Results obtained analytically and verified through simulations show that, in terms of the symbol error probability, the proposed PAM constellations outperforms conventional uniform PAM constellation as well as the other models of piecewise‐uniform PAM constellations.

In this letter, asymptotic formulas are derived for signal to quantization noise ratio (SQNR) of two unrestricted polar quantizers (UPQs) for the case where designed-for and applied-to Gaussian sources have different variances. It is shown that the limitation in the variance mismatch analysis observed in one of the UPQs can be overcome by the constrained application of asymptotic approximations and by optimizing the last magnitude reconstruction level subsequently. The derived formulas are a useful analytical tool for determining the effect of variance mismatch on SQNR in unrestricted polar quantization for Gaussian source.

An optimized vector-quantization-inspired signal constellation design (OVQ-SCD) suitable for multidimensional optical transport is proposed, in which signal constellation radii transformation function is optimized and near-uniform distribution of points is achieved. The proposed OVQ-SCD is used in a tandem with a hybrid multidimensional coded-modulation scheme employing Slepian sequences as electrical discrete-time basis functions, orthogonal prolate spheroidal wave functions as impulse responses of optical filters in orthogonal-division multiplexing, and spatial modes as optical continuous-time basis functions. It has been shown that the proposed multidimensional coded-modulation schemes based on OVQ-SCDs outperform corresponding counterparts and can be used to enable beyond 10 Pb/s serial optical transport over spatial division multiplexing (SDM) fibers as well as beyond 1 Pb/s transport over SMFs. The proposed OVQ-SCD-based hybrid multidimensional coded modulation scheme can simultaneously solve the problems related to the limited bandwidth of information-infrastructure, high energy consumption, and heterogeneity of network segments; while enabling elastic and dynamic bandwidth allocation.