An adaptive deconvolution smoothing filter implemented on a multiple transputer network
0
Citation
0
Reference
20
Related Paper
Abstract:
A multiple transputer system is demonstrated to work in handling adaptive deconvolution smoothing. The cooperation between its four units allow the separate tasks of data I/O, parameter estimation and smoothing filter to proceed in parallel, with the different data items and parameters being passed across the transputer channels connecting the four units. Although the performance of the transputer system was found to be slow compared to the TMS32010 system, the hardware and software flexibility provided by the transputer did allow the easy integration of a supervisor into the system. The use of a supervisor is shown to enhance the robustness of an adaptive signal processor. From the evaluation, the transputer would be well suited to applications within adaptive control. Future research will consider the application of supervisor transputers to adaptive control problems. >Keywords:
Transputer
Smoothing
Supervisor
Robustness
Cite
Cite
Citations (4)
A real-time adaptive lattice predictor was implemented using a digital signal processing chip. The implementation comprises input-output units, a central processing and control unit, and supporting software. The performance of the hardware was verified by comparing an input signal and the one-step prediction signal calculated by the predictor. The maximum operating frequency for the four-stage lattice structure was 13.5 kHz.< >
Lattice (music)
Cite
Citations (3)
An experimental, general purpose adaptive signal processor system has been developed, utilizing a quantized (clipped) version of the Widrow-Hoff least-mean-square adaptive algorithm developed by Moschner. The system accommodates 64 adaptive weight channels with 8-bit resolution for each weight. Internal weight update arithmetic is performed with 16-bit resolution, and the system error signal is measured with 12-bit resolution. An adapt cycle of adjusting all 64 weight channels is accomplished in 8 ..mu..sec. Hardware of the signal processor utilizes primarily Schottky-TTL type integrated circuits. A prototype system with 24 weight channels has been constructed and tested. This report presents details of the system design and describes basic experiments performed with the prototype signal processor. Finally some system configurations and applications for this adaptive signal processor are discussed.
SIGNAL (programming language)
Cite
Citations (0)
Transputer
Supervisor
Smoothing
SIGNAL (programming language)
Cite
Citations (0)
The paper presents an approach to implementing the parallel Kalman filter. The parallel Kalman filter is computationally intensive and hence complex due to the inherent matrix operations. Often, the filter cannot be computed in real time when the system has a large number of state variables. A method is discussed for achieving almost real-time performance. In addition, a method for determining stability of the Kalman filter is presented. This method involves the use a paradigm that achieves high performance and close to real time results while maintaining accuracy for the Kalman filter. In addition, the paradigm shows an improvement of the processor utilization over other implementations and provides flexibility in terms of the hardware used for implementation.
Alpha beta filter
Implementation
Cite
Citations (10)
Cite
Citations (4)
Multichannel adaptive equalization (AE) systems require high computational capacity, which constraints their practical implementation. Graphics Processing Units (GPUs) are well known due to their potential for highly parallel data processing. Although the GPUs seem to be suitable platforms for multichannel scenarios, an efficient use of parallel computation in the adaptive filtering context is not straightforward due to the feedback loops. This paper presents a GPU implementation of a multichannel AE system based on the filtered-x LMS algorithm working over a real-time prototype. Details of the parallelization of the algorithm are given. Experimental results are presented to validate and computationally analyze the real-time performance of the AE GPU implementation. Results show the usefulness of GPUs to develop versatile, scalable and low cost multichannel AE systems.
Graphics processing unit
Cite
Citations (4)
SIGNAL (programming language)
Cite
Citations (1)
The FDSP (Fuzzy Digital Signal Processor) is a new device that combines fuzzy processor and DSP in a single core well adapted to be hosted by low cost microcontrollers. The FDSP offers economic solution to implement adaptive fuzzy digital signal processing. The fuzzy processor acts as a controller or an adaptive element to a DSP system to implement adaptive filters, noise cancellers, estimators, channel equalizers, etc. We demonstrate the use of the FDSP to implement hard disk drive controller that combines quasi-optimum seek-track control, adaptive noise filters, and velocity estimator. Other applications of the FDSP include non-linear imaging filters and motion estimators and other systems for multimedia processing.
Cite
Citations (4)
Two multi-digital-signal-processor systems for high-speed signal processing are presented. Both systems can be configured with a variable number of processor units. Thus, there is sufficient computational power for real-time implementations of high-order adaptive filter algorithms as required for echo cancellation, e.g. in hands-free telephone equipment. One system is based on the DSP32 floating-point DSP (digital signal processor) from AT&T. Monitoring and debugging is done with a standard PC system. The second system uses Fujitsu's MB8764 fixed-point DSP. It is controlled by an 80186 AMS-M-Bus microcomputer board. The architectures are designed to support efficient parallel implementations of high-order adaptive algorithms and of multirate systems for echo compensation in frequency subbands (i.e. block processing).< >
Echo (communications protocol)
SIGNAL (programming language)
Micro computer
Cite
Citations (4)