The Experts below are selected from a list of 117765 Experts worldwide ranked by ideXlab platform

Manabendra Bhuyan - One of the best experts on this subject based on the ideXlab platform.

  • abp peak detection using Energy Analysis Technique
    2011
    Co-Authors: Awadhesh Pachauri, Manabendra Bhuyan
    Abstract:

    This paper describes an algorithm for the automatic detection of systolic peaks in the Arterial Blood Pressure (ABP) signal. ABP waveform is rich in pathological information such as heart rate, systolic, mean and diastolic pressure therefore it is very important for clinical diagnosis in cardiology. The proposed algorithm deals with the development of Energy based Technique for the detection of systolic peaks in ABP signal that is of great importance in evaluating heart rate computation and serves as the basis for the extraction of other ABP features. The algorithm has been developed based on the window based Energy Analysis of ABP signal. This Energy domain offers an easy interpretation of the ABP signal for the detection of systolic peaks in ABP signal. The ABP signal under test undergoes window based Energy Analysis by selecting a window of 100 ms duration. The window is shifted along time axis and the Energy of samples falling in the succeeding window is calculated. The areas in ABP signal where systolic peaks are available appear as high Energy zones. Window based amplitude threshold and interval threshold are applied to reject the unwanted peaks. The algorithm is easier to implement just after removal of the low frequency samples in ABP signal. ABP signals are downloaded from MGH/MF waveform database and algorithm has been developed on five minute segment of ABP signals. The method has been validated based on beat annotations of five minute segment of corresponding ECG signal from modified lead II.

Gregor Tanner - One of the best experts on this subject based on the ideXlab platform.

  • solving the stationary liouville equation via a boundary element method
    2013
    Co-Authors: D J Chappell, Gregor Tanner
    Abstract:

    Energy distributions of linear wave fields are, in the high frequency limit, often approximated in terms of flow or transport equations in phase space. Common Techniques for solving the flow equations in both time dependent and stationary problems are ray tracing and level set methods. In the context of predicting the vibro-acoustic response of complex engineering structures, related methods such as Statistical Energy Analysis or variants thereof have found widespread applications. We present a new method for solving the transport equations for complex multi-component structures based on a boundary element formulation of the stationary Liouville equation. The method is an improved version of the Dynamical Energy Analysis Technique introduced recently by the authors. It interpolates between standard statistical Energy Analysis and full ray tracing, containing both of these methods as limiting cases. We demonstrate that the method can be used to efficiently deal with complex large scale problems giving good approximations of the Energy distribution when compared to exact solutions of the underlying wave equation.

Awadhesh Pachauri - One of the best experts on this subject based on the ideXlab platform.

  • abp peak detection using Energy Analysis Technique
    2011
    Co-Authors: Awadhesh Pachauri, Manabendra Bhuyan
    Abstract:

    This paper describes an algorithm for the automatic detection of systolic peaks in the Arterial Blood Pressure (ABP) signal. ABP waveform is rich in pathological information such as heart rate, systolic, mean and diastolic pressure therefore it is very important for clinical diagnosis in cardiology. The proposed algorithm deals with the development of Energy based Technique for the detection of systolic peaks in ABP signal that is of great importance in evaluating heart rate computation and serves as the basis for the extraction of other ABP features. The algorithm has been developed based on the window based Energy Analysis of ABP signal. This Energy domain offers an easy interpretation of the ABP signal for the detection of systolic peaks in ABP signal. The ABP signal under test undergoes window based Energy Analysis by selecting a window of 100 ms duration. The window is shifted along time axis and the Energy of samples falling in the succeeding window is calculated. The areas in ABP signal where systolic peaks are available appear as high Energy zones. Window based amplitude threshold and interval threshold are applied to reject the unwanted peaks. The algorithm is easier to implement just after removal of the low frequency samples in ABP signal. ABP signals are downloaded from MGH/MF waveform database and algorithm has been developed on five minute segment of ABP signals. The method has been validated based on beat annotations of five minute segment of corresponding ECG signal from modified lead II.

D J Chappell - One of the best experts on this subject based on the ideXlab platform.

  • solving the stationary liouville equation via a boundary element method
    2013
    Co-Authors: D J Chappell, Gregor Tanner
    Abstract:

    Energy distributions of linear wave fields are, in the high frequency limit, often approximated in terms of flow or transport equations in phase space. Common Techniques for solving the flow equations in both time dependent and stationary problems are ray tracing and level set methods. In the context of predicting the vibro-acoustic response of complex engineering structures, related methods such as Statistical Energy Analysis or variants thereof have found widespread applications. We present a new method for solving the transport equations for complex multi-component structures based on a boundary element formulation of the stationary Liouville equation. The method is an improved version of the Dynamical Energy Analysis Technique introduced recently by the authors. It interpolates between standard statistical Energy Analysis and full ray tracing, containing both of these methods as limiting cases. We demonstrate that the method can be used to efficiently deal with complex large scale problems giving good approximations of the Energy distribution when compared to exact solutions of the underlying wave equation.

Balachandran Neerajnayan - One of the best experts on this subject based on the ideXlab platform.

  • Low power memory controller subsystem IP exploration using RTL power flow : An End-to-end power Analysis and reduction Methodology
    2020
    Co-Authors: Balachandran Neerajnayan
    Abstract:

    With FinFET based Application Specific Integrated Circuit (ASIC) designs delivering on the promises of scalability, performance, and power, the road ahead is bumpy with technical challenges in building efficient ASICs. Designers can no longer rely on the ‘auto-scaling’ power reduction that follows technology node scaling, in these times when 7nm presents itself as a ‘long-lived’ node. This leads to the need for early power Analysis and reduction flows that are incorporated into the ASIC Intellectual Property (IP) design flow. This leads to a focus on power-efficient design in addition to being functionally efficient. Power inefficiency related hotspots are the leading causes of chip re-spins, and a guideline methodology to design blocks in a power-efficient manner leads to a power-efficient design of the Integrated Circuits (ICs). This alleviates the intensity of cooling requirements and the cost. The Common Memory controller is one of the leading consumers of power in the ASIC designs at Ericsson. This Thesis focusses on developing a power Analysis and reduction flow for the common memory controller by connecting the verification environment of the block to low-level power Analysis tools, using motivated test cases to collect power metrics, thereby leading to two main goals of the Thesis, characterization and optimization of the block for power. This work also includes an Energy efficiency perspective through the Differential Energy Analysis Technique, initiated by Qualcomm and Ansys, to improve the flow by improving the test cases that help uncover power inefficiencies/bugs and therefore optimize the block. The flow developed in the Thesis fulfills the goals of characterizing and optimizing the block. The characterization data is presented to provide an idea of the type of data that can be collected and useful for SoC architects and designers in planning for future designs. The characterization/profiling data collected from the blocks collectively contribute to the Electronic System-level power Analysis that helps correlate the ASIC power estimate to silicon. The work also validates the flow by working on a specific sub-block, identifying possible power bugs, modifying the design and validating improved performance and thereby, validating the flow.Med FinFET-baserade applikationsspecifika integrerade kretsar (ASIC) -konstruktioner som ger löften om skalbarhet, prestanda och kraft är vägen framåt ojämn med tekniska utmaningar när det gäller att bygga effektiva ASIC: er. Formgivare kan inte längre lita på den "autoskalande" effektminskningen som följer teknisk nodskalning, i dessa tider då 7nm presenterar sig som en "långlivad" nod. Detta leder till behovet av tidig kraftanalys och reduktionsflöden som är integrerade i ASIC Intellectual Property (IP) designflöde. Detta leder till fokus på energieffektiv design förutom att det är funktionellt effektivt. Krafteffektivitetsrelaterade hotspots är de ledande orsakerna till respins av chip, och en riktlinjemetodik för att konstruera block på ett energieffektivt sätt leder till energieffektiv design av Integrated Circuits (ICs). Detta lindrar intensiteten hos kylbehovet och kostnaden. Common Memory-kontrollen är en av de ledande energikonsumenterna i ASIC-designen hos Ericsson. Denna avhandling fokuserar på att utveckla en effektanalys och reduktionsflöde för den gemensamma minneskontrollern genom att ansluta verifieringsmiljön för blocket till lågnivåeffektanalysverktyg, med hjälp av motiverade test caser för att samla effektmätvärden, vilket leder till två huvudmål för avhandlingen, karakterisering och optimering av blocket för kraft. Detta arbete inkluderar också energieffektivitetsperspektiv genom Differential Energy Analys-teknik, initierad av Qualcomm och Ansys, för att förbättra flödet genom att förbättra test cases som hjälper till att upptäcka effekteffektivitet / buggar och därför optimera blocket. Flödet som utvecklats i avhandlingen uppfyller målen att karakterisera och optimera blocket. Karaktäriseringsdata presenteras för att ge en uppfattning om vilken typ av data som kan samlas in och vara användbara för SoC-arkitekter och designers i planering för framtida mönster. Karaktäriserings/ profileringsdata som samlats in från blocken bidrar tillsammans till effektanalysen för elektronisk systemnivå som hjälper till att korrelera ASIC-effektberäkningen till kisel. Arbetet validerar också flödet genom att arbeta på ett specifikt underblock, identifiera möjliga effektbuggar, modifiera utforma och validera förbättrad prestanda och därmed validera flödet