The implementation of the Kalman filter using systolic architectures is considered. Using an orthogonal array processor, an algorithm is presented which increases the throughput of matrix operations with no additional hardware. The algorithm makes use of high-level pipelining so that loading process and arithmetic operations can be performed simultaneously, yielding higher peripheral equipment utilization and faster performance
The implementation of matrix inversion algorithms using the few instructions, multiple data, systoli...
Optimization is listed as one of the important topics in today’s electronic system due to the presen...
Concise algorithms to compute a solution of a system of m linear equations Ax=b with n variables are...
An important part of optimal estimation technology, the Kalman filter is a computationally intensive...
A novel two-dimensional parallel computing method for real-time Kalman filtering is presented. The m...
The Kalman filter is an important component of optimal estimation theory. It has applications in a w...
In this paper we propose a pipelined structure for systolic array-based matrix inversion. The main f...
The Kalman filter is a very commonly used signal processing tool for estimating state variables from...
Abstract:- Based on the fact that Faddeev’s algorithm can be easily mapped into the Systolic array f...
Includes bibliographical references.Two sets of block Kalman filtering equations are derived that di...
This paper presents a parametrized VLSI architecture for an nstate Kalman filter implementation inte...
This thesis presents some new systolic algorithms for numerical computation, that are suitable for i...
Graduation date: 1989Digital signal and image processing and other real time\ud applications involve...
This thesis discusses and presents the design of systolic arrays used in modern real time signal pro...
The Kalman filter is a set of mathematical equations that provides an efficient computational (recur...
The implementation of matrix inversion algorithms using the few instructions, multiple data, systoli...
Optimization is listed as one of the important topics in today’s electronic system due to the presen...
Concise algorithms to compute a solution of a system of m linear equations Ax=b with n variables are...
An important part of optimal estimation technology, the Kalman filter is a computationally intensive...
A novel two-dimensional parallel computing method for real-time Kalman filtering is presented. The m...
The Kalman filter is an important component of optimal estimation theory. It has applications in a w...
In this paper we propose a pipelined structure for systolic array-based matrix inversion. The main f...
The Kalman filter is a very commonly used signal processing tool for estimating state variables from...
Abstract:- Based on the fact that Faddeev’s algorithm can be easily mapped into the Systolic array f...
Includes bibliographical references.Two sets of block Kalman filtering equations are derived that di...
This paper presents a parametrized VLSI architecture for an nstate Kalman filter implementation inte...
This thesis presents some new systolic algorithms for numerical computation, that are suitable for i...
Graduation date: 1989Digital signal and image processing and other real time\ud applications involve...
This thesis discusses and presents the design of systolic arrays used in modern real time signal pro...
The Kalman filter is a set of mathematical equations that provides an efficient computational (recur...
The implementation of matrix inversion algorithms using the few instructions, multiple data, systoli...
Optimization is listed as one of the important topics in today’s electronic system due to the presen...
Concise algorithms to compute a solution of a system of m linear equations Ax=b with n variables are...