While SAT-based algorithms have largely displaced BDD-based verification techniques due to their typically higher scalability, there are classes of problems for which BDDbased reachability analysis is the only existing method for an automated solution. Nonetheless, reachability engines require a high degree of tuning to perform well on challenging benchmarks. In addition to clever partitioning ...

In this paper we describe the design of a voice-enabled interface embedded in a Personal Digital Assistant (PDA). It is a component of a more complex system which allows the access to real-time information (for example, prices on stock exchange) via the General Packet Radio Service (GPRS). Specifically, we have focused on the Automatic Speech Recognition (ASR) module: we have implemented a fixe...

In this paper, we present a novel method for designing polynomial-predictive FIR differentiators for fixed-point environments. Our method yields filters that exactly fulfill the given constraints even with short coefficient word lengths. Under ordinary quantization, either by rounding or truncation, these filters in most cases loose their predictive and/or differentiating properties, making the...

In this paper, we develop a multidimensional companding scheme for the preceptual distortion measure by S. van de Par [1]. The scheme is asymptotically optimal in the sense that it has a vanishing rate-loss with increasing vector dimension. The compressor operates in the frequency domain: in its simplest form, it pointwise multiplies the Discrete Fourier Transform (DFT) of the windowed input si...

A simple tuning scheme that shifts the crossover frequency of the start-up IIR half-band filter pair to the desired location has been introduced recently. In this paper, the approximation of the tuning scheme is derived in a manner that makes this scheme suitable for fixedpoint arithmetic. The effects of the approximation error to the frequency responses and to the complementary properties for ...

Latent Gaussian Models (LGM) provide a rich modeling framework with general inference procedures. The variational approximation offers an effective solution for such models and has attracted a significant amount of interest. Recent work proposed a fixedpoint (FP) update procedure to optimize the covariance matrix in the variational solution and demonstrated its efficacy in specific models. The ...

The model-checking games associated with fixed-point logics are parity games, and it is currently not known whether the strategy problem for parity games can be solved in polynomial time. We study Solitaire-LFP, a fragment of least fixedpoint logic, whose evaluation games are nested soltaire games. This means that on each strongly connected component of the game, only one player can make nontri...

Training neural networks is a timeand compute-intensive operation. This is mainly due to the large amount of floating point tensor operations that are required during training. These constraints limit the scope of design space explorations (in terms of hyperparameter search) for data scientists and researchers. Recent work has explored the possibility of reducing the numerical precision used to...

Echo State Networks (ESN) have demonstrated their efficiency in supervised learning of time series: a ”reservoir” of neurons provide a set of dynamical systems that can be linearly combined to match the target dynamics, using a simple quadratic optimisation algorithm to tune the few free parameters. In an unsupervised learning context, however, another optimiser is needed. In this paper, an ada...

In this paper, we present a Catapult C/C++ based methodology that integrates key technologies for high-level VLSI modelling of 3G/4G wireless systems to enable extensive time/area tradeoff study. A Catapult C/C++ based architecture scheduler transfers the major workload to the algorithmic C/C++ fixedpoint design. Prototyping experiences are presented to explore the VLSI design space extensively...