Ganguli (aerospace engineering, Indian Institute of Science) here outlines novel methods, including those based on Kalman filters, neural networks and fuzzy logic that focus on removing extraneous noise.
What does KF stand for?
KF stands for Kalman Filter
This definition appears very frequently and is found in the following Acronym Finder categories:
- Information technology (IT) and computers
- Science, medicine, engineering, etc.
See other definitions of KF
We have 11 other meanings of KF in our Acronym Attic
- Keying Material
- Kamenori Earth Youth Summit (Japan)
- Keep Educating Yourself and Staff (various locations)
- Keep Empowering Yourself Successfully
- Keeping Every Youth in School (Corpus Christi, TX)
- Kingdom Education for Young Scholars (Virginia Beach, VA)
- Kingston Employment Youth Services (Canada)
- Kosciusko Endowment Youth Services (Warsaw, IN)
- Kontrola Ekologického Zemedelství (Czech: Control of Organic Farming; inspection and certification; est. 1999; Chrudim, Czech Republic)
- Kosovo Engagement Zone
Samples in periodicals archive:
As an invariant estimation algorithm, the optimal Kalman filter is applied.
2004) introduced a dynamic model consisting of an artificial neural network model and the Kalman filter technique to predict bus arrival times based on data collected by a real world APC.
Following Harvey (1989) and Ogawa and Sakane (2006), the estimated structure of the currency basket with time-varying weights is estimated using the Kalman filter in the following form: [DELTA][e.
The Kalman Filter assumes the process being driven by Gaussian noise.
Keywords: speech signal, clipped speech, restoration, interpolation, linear prediction, least square method, Kalman filter 1 Introduction Speech acquired by personal computer sound cards is often confronted with two main problems: DC level wandering and peak clipping.
When the state variables (including output gap, potential output, or both) and the system parameters are to be estimated simultaneously in a time-varying fashion, the model takes a nonlinear characteristic, and the standard Kalman filter (SKF) needs to be modified.
Its built-in Enhanced Kalman Filter algorithm uses a combination of GPS and dead reckoning data that counters the respective disadvantages of each approach.