We present a new way of modelling the Precedence Effect to enable the robust measurement of localization cues (ITD and IID) in echoic environments. Based on this we developed a localization system which is inspired by...
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ISBN:
(纸本)9781604234497
We present a new way of modelling the Precedence Effect to enable the robust measurement of localization cues (ITD and IID) in echoic environments. Based on this we developed a localization system which is inspired by the auditory system of mammals. It uses a Gammatone filter bank for preprocessing and extracts the ITD cue via zero crossings (IID calculation is straight forward). The mapping between the cue values and the different angles is learned offline which facilitates the adaptation to different head geometries. The performance of the system is demonstrated by localization results for two simultaneous speakers and the mixture of a speaker, music, and fan noise in a normal meeting room. A real-time demonstrator of the system is presented in [1].
In this paper we will discuss about a problematical using multi-agent system (MAS) for resolving the problem scheduhng production. The basic idea for achieving global optimal solution is a coordinating all agents to r...
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In this paper we will discuss about a problematical using multi-agent system (MAS) for resolving the problem scheduhng production. The basic idea for achieving global optimal solution is a coordinating all agents to resolve (in our case each producer is considered as one autonomous agent). Each agent possesses own goal but it can Improve own goal by coordinating with another or help another one to achieve its goal. We will analyze what may bnng the coordmatlon between agents and propose several mechanisms for coordination. Also we will discuss about a methods of evaluating bid that the agents order between themselves
In this paper, we present a generic way to use a hierarchical representation of prediction models for adaptive tracking. Starting with a basic appearance-based tracker working in 2D retinal space, we show how to combi...
ISBN:
(纸本)2930307102
In this paper, we present a generic way to use a hierarchical representation of prediction models for adaptive tracking. Starting with a basic appearance-based tracker working in 2D retinal space, we show how to combine individual trackers for the left and right eye to a true 3D tracker that is built on top of the 2D trackers. We show how the trackers benefit from the hierarchical structure by dynamical model switching depending on the reliability of the tracking results.
Here are described the problems of analytical calculation some parameters of AAAS with SRF using ergodic theory, and mathematical conections allowing handle long-run behavior. The conditions allowing to use the long-r...
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Here are described the problems of analytical calculation some parameters of AAAS with SRF using ergodic theory, and mathematical conections allowing handle long-run behavior. The conditions allowing to use the long-run behavior to this calculation according to the article ***, GSMP Formalism for DES, (1989) are considered as requiriments on structural properties of the system.
In this paper, we propose two variants of adaptive state space controllers for attitude stabilization and self-tuning of a four-rotor aerial robot, a quadrotor. First of all, the use of a Model Identification Adaptive...
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In this paper, we propose two variants of adaptive state space controllers for attitude stabilization and self-tuning of a four-rotor aerial robot, a quadrotor. First of all, the use of a Model Identification Adaptive controller (MIAC) is proposed in terms of combining a recursive least-squares estimator with exponential forgetting with an integral discrete-time state space controller. Furthermore, a continuous-time Model Reference Adaptive control (MRAC) scheme based on Lyapunov theory is applied to the simplified dynamics of a quadrotor, which guarantees global asymptotic stability for at least linear overall systems. The effectiveness of the suggested adaptive methods is demonstrated in simulations with a quaternion-based nonlinear dynamic model of a quadrotor derived in this work. The results are compared to a designed nonadaptive integral state space controller.
The topic of the paper is the scheduling problem of jobs in multi-machine multi-part manufacturing systems. In the paper the approach to the creation of the scheduling algorithm using the multi-agent rules is describe...
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The topic of the paper is the scheduling problem of jobs in multi-machine multi-part manufacturing systems. In the paper the approach to the creation of the scheduling algorithm using the multi-agent rules is described. In the simulation phase, graphical representation of the scheduling problem by the statecharts model is used to detect the conflict situations.
We propose a new set point tracking controller for plants subject to simultaneous input amplitude and rate constraints. Short settling times are achieved by allowing the controller to saturate. The tracking controller...
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We propose a new set point tracking controller for plants subject to simultaneous input amplitude and rate constraints. Short settling times are achieved by allowing the controller to saturate. The tracking controller can be deduced from a controller stabilizing the origin with an associated domain of attraction. Additionally, no assumptions concerning the rate of the reference signal are necessary.
In this paper, a computational approach for controller design for polynomial systems with input constraints is proposed. The design is formulated as a convex optimization problem and capable of dealing with asymmetric...
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In this paper, a computational approach for controller design for polynomial systems with input constraints is proposed. The design is formulated as a convex optimization problem and capable of dealing with asymmetric input constraints. The idea of the method is to combine the recently introduced notion of virtual inputs and the notion of feedback passivity to obtain an optimization problem with polynomial constraints. The optimization problem is relaxed using the method of sum of squares which finally results in an LMI problem. The resulting state feedback controllers are non-polynomial. The approach contains some conservatism arising when formulating the design as a convex optimization problem. The introduction of slack variables and a postprocessing step reduces this conservatism. The applicability of the method is demonstrated by a controller design for a jet engine compressor.
The paper deals with new developments of interpolating memories as the basic element of learning control and with their possible application. It discusses learning control, interpolating memories, characteristic manif...
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The paper deals with new developments of interpolating memories as the basic element of learning control and with their possible application. It discusses learning control, interpolating memories, characteristic manifolds for automotive control, and possible future developments.< >
This paper proposes a new approach to system modeling using continuous-time recurrent fuzzy systems (CTRFS). The approach is based on the representation of CTRFS as hybrid systems. With this representation, various fo...
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This paper proposes a new approach to system modeling using continuous-time recurrent fuzzy systems (CTRFS). The approach is based on the representation of CTRFS as hybrid systems. With this representation, various forms of a priori knowledge about the system to be modeled can be incorporated. This allows a reasonable reduction of optimization parameters and hence, avoids overfitting. Furthermore, the presented approach offers a deeper insight into the system structure on the basis of measurement data solely. This is illustrated by a selection algorithm for relevant input and state variables. The applicability of the approach is shown by modeling a chemical process.
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