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On Monday, Tier 1 suppliers Continental and ZF announced that by 2020 they will have partially automated driving systems ready for production that are based on the Drive AutoPilot platform.
I know this drive so well that I plan our pit stops based on the drive through Starbucks locations.
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Remark 4 Based on the drive-response concept, synchronization problems of discrete-time neural networks are little investigated.
It proposes a fast mechanism for synchronizing the transmitter and the receiver that is based on the drive-response approach.
First we introduce some definitions, then we propose a fast mechanism for synchronization the chaotic systems without linear term (11) based on the drive-response approach.
This paper establishes the indicators to evaluate the sustainability of water utilization based on the Drive-Pressure-Status-Impact-Response (DPSIR) model.
Based on the drive-response concept and the Lyapunov stability theorem, a memoryless decentralized control law is proposed which guarantees exponential synchronization even when input nonlinearity is present.
Based on the drive-response concept and the Lyapunov stability theorem, a linear matrix inequality (LMI) approach is given to establish sufficient conditions under which the considered neural networks are globally asymptotically synchronized in the mean square.
In Section 3, based on the drive-response concept and the Lyapunov functional method, we discuss global asymptotical synchronization in mean square for uncertain stochastic discrete-time delayed neural networks with mixed delays.
Based on the drive-in rack impact test results presented in a companion paper (Gilbert and Rasmussen, submitted for publication) [1] and the simple mechanical models for drive-in racks, actual impact forces are calculated and presented.
Based on the drive-response concept, the stochastic differential inclusions theory and the Lyapunov functional method with the impulsive delay differential inequality technique was established to guarantee the impulsive synchronization of memristor-based recurrent neural networks with stochastic effects.
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