1,105 research outputs found
Differential games with asymmetric information and without Isaacs condition
We investigate a two-player zero-sum differential game with asymmetric
information on the payoff and without Isaacs condition. The dynamics is an
ordinary differential equation parametrised by two controls chosen by the
players. Each player has a private information on the payoff of the game, while
his opponent knows only the probability distribution on the information of the
other player. We show that a suitable definition of random strategies allows to
prove the existence of a value in mixed strategies. Moreover, the value
function can be characterised in term of the unique viscosity solution in some
dual sense of a Hamilton-Jacobi-Isaacs equation. Here we do not suppose the
Isaacs condition which is usually assumed in differential games
Specification tests for temporal heterogeneity in spatial panel data models with fixed effects
Singapore Management Universit
PCNN: A Lightweight Parallel Conformer Neural Network for Efficient Monaural Speech Enhancement
Convolutional neural networks (CNN) and Transformer have wildly succeeded in
multimedia applications. However, more effort needs to be made to harmonize
these two architectures effectively to satisfy speech enhancement. This paper
aims to unify these two architectures and presents a Parallel Conformer for
speech enhancement. In particular, the CNN and the self-attention (SA) in the
Transformer are fully exploited for local format patterns and global structure
representations. Based on the small receptive field size of CNN and the high
computational complexity of SA, we specially designed a multi-branch dilated
convolution (MBDC) and a self-channel-time-frequency attention (Self-CTFA)
module. MBDC contains three convolutional layers with different dilation rates
for the feature from local to non-local processing. Experimental results show
that our method performs better than state-of-the-art methods in most
evaluation criteria while maintaining the lowest model parameters.Comment: Accepted at INTERSPEECH 202
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