Convergence Improving in Evolution–Based Technique for Estimation and Separation of Electrooculography and Blinking Signals

Krupiński, Robert; Mazurek, P.

doi:10.1007/978-3-642-13105-9_30

Cited by 3 publications

(7 citation statements)

References 17 publications

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“…8). Such a technique is based on fitting a signal generator model to a signal using the optimization techniques [Krupiński & Mazurek (2010b;e;]. The additional constraints are added for improving results and for the reduction of computation time.…”

Section: Analysis By Synthesis Techniquementioning

confidence: 99%

“…The samples obtained by the real measurement process are related to the small set of humans. The EOG and blinking signals generator is described in [Krupiński & Mazurek (2010a)] and used in the papers [Krupiński & Mazurek (2010b;e;] with some additional extensions (the smooth pursuit support). There are two possible techniques for the application of the generator.…”

Section: Monte Carlo Approach and A Signal Generatormentioning

confidence: 99%

“…The estimation of the blink and EOG signals is important for the real-time HCI systems. Previous work related to the optimization approach [Krupiński & Mazurek (2010b;e;], using the blinking and eye movement model, was not well fitted for the real-time processing. The computation requirements were high and not defined by the number of processing steps due to the applications of the random number generator in the optimization algorithm.…”

Section: Conclusion and Further Workmentioning

confidence: 99%

“…The computation time was also reduced by the reduction of the number of processed samples. The blink and saccade positions were also considered as a starting point for the optimization process near the global minima [Krupiński & Mazurek (2010b)] and the sensitivity of this approach was considered in [Krupiński & Mazurek (2010e)]. Additionally, the estimation of the smooth pursuit movements was observed to improve the results [Krupiński & Mazurek (2010d)].…”

Section: Conclusion and Further Workmentioning

confidence: 99%

See 3 more Smart Citations

Real-Time Low-Latency Estimation of the Blinking and EOG Signals

́nski¹,

Mazurek²

2012

Real-Time Systems, Architecture, Scheduling, and Application

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Section: Analysis By Synthesis Techniquementioning

confidence: 99%

Section: Monte Carlo Approach and A Signal Generatormentioning

confidence: 99%

Section: Conclusion and Further Workmentioning

confidence: 99%

Section: Conclusion and Further Workmentioning

confidence: 99%

See 2 more Smart Citations

Real-Time Low-Latency Estimation of the Blinking and EOG Signals

́nski¹,

Mazurek²

2012

Real-Time Systems, Architecture, Scheduling, and Application

View full text Add to dashboard Cite

“…8). Such a technique is based on fitting a signal generator model to a signal using the optimization techniques [Krupiński & Mazurek (2010b;]. The additional constraints are added for improving results and for the reduction of computation time.…”

Section: Analysis By Synthesis Techniquementioning

confidence: 99%

Real-Time Systems, Architecture, Scheduling, and Application

Babamir¹

2012

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Real-Time Systems are computing systems that must meet their temporal specification. In computer science, real-time or reactive computing is the study of hardware and software systems that are subject to a real-time constraint called deadline, which the system should respect it in its response to events. Real-time systems, in fact, must guarantee response within strict time constraints. Real-time systems often appear as critical systems such as mission critical ones. The anti-lock brakes system on a car, for instance, is a real-time computing system where the real-time constraint is the brakes release time to prevent the wheel from locking. Real-time software may use synchronous programming languages, real-time operating systems and real-time networks providing essential frameworks for constructing real-time software applications.X Preface (Chapters 1 to 4) on real-time architectures and continues with a section (Chapters 5 and 6) on specification and verification of real-time systems, a section on real-time scheduling algorithms (Chapters 7 to 9) and ends with a section (Chapters 10 to 15) on some real world application of real-time systems.Section 1 consisting of Chapters 1 to 4 deals with architectures of real-time systems. Chapter 1 presents realizing the networking applications by means of DSP microcomputer architecture (Blackfin microcomputer) supported by an operating system kernel (Visual DSP Kernel) and lightweight IP protocol stack (LWIP suite). Moreover, the chapter provides the frameworks for telecommunications applications development and for performance evaluation. A VoIP (Voice over IP) system, as a complex networking application example, is illustrated based on adaptive multi-rate codec.Preface XI Also, this chapter proposes an approach to specify real-time systems having some features. To this end, it extends the UML sequence diagrams with new kinds of stereotypes and the notion of monitoring scenarios is introduced. Monitoring scenarios are also specified by sequence diagrams used to define liveness and safety properties.Chapter 6 provides a method for specifying and stating real-time software using Timed Automata and Real-time Logic respectively. Then, the chapter deals with obtaining the safety constraints from reachability graph of Timed Automata extracted from the problem specification and then the constraints are stated in Real-time Logic propositions. These propositions showing safety constraints are used for verification of the system behavior. To show the effectiveness of the proposed method, the chapter sets it forth for a real-time system called Rail Road Crossing Control. This chapter also includes a brief explanation of Timed Automata and Real-time Logic and a method is presented to simulate Timed Automata in Real-time logic.Section 3 consisting of Chapters 7 to 9 deals with scheduling discussion in real-time systems. Chapter 7 addresses the problem of handling overload conditions in real-time systems. The conditions are critical situations in which the computational demand requested...

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Estimation of Electrooculography and Blinking Signals Based on Filter Banks

Krupiński

Mazurek

2012

Computer Vision and Graphics

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Convergence Improving in Evolution–Based Technique for Estimation and Separation of Electrooculography and Blinking Signals

Cited by 3 publications

References 17 publications

Real-Time Low-Latency Estimation of the Blinking and EOG Signals

Real-Time Low-Latency Estimation of the Blinking and EOG Signals

Real-Time Systems, Architecture, Scheduling, and Application

Estimation of Electrooculography and Blinking Signals Based on Filter Banks

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