Results 51 to 60 of about 369 (198)
Quantized Output Feedback Stabilization by Luenberger Observers
IFAC-PapersOnLine, 2017 We study a stabilization problem for systems with quantized output feedback. The state estimate from a Luenberger observer is used for control inputs and quantization centers. First we consider the case when only the output is quantized and provide data-rate conditions for stabilization.
Masashi Wakaiki +2 more
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On the Role of Preprocessing and Memristor Dynamics in Reservoir Computing for Image Classification
Advanced Electronic Materials, EarlyView.ABSTRACT Reservoir computing (RC) is an emerging recurrent neural network architecture that has attracted growing attention for its low training cost and modest hardware requirements. Memristor‐based circuits are particularly promising for RC, as their intrinsic dynamics can reduce network size and parameter overhead in tasks such as time‐series ...
Rishona Daniels +4 more
wiley +1 more source
Beamforming matrix quantization with variable feedback rate
2008 IEEE 19th International Symposium on Personal, Indoor and Mobile Radio Communications, 2008 We propose an improved beamforming matrix compression by Givens Rotation with the use of variable feedback rate. The variable feedback rate means that the number of bits used to represent the quantized beamforming matrix is based on the value of the matrix. Compared with the fixed feedback rate scheme, the proposed method has better performance without
Chau Yuen, Sumei Sun, Mel Meau Shin Ho
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Advanced Intelligent Discovery, EarlyView.Capacitive, charge‐domain compute‐in‐memory (CIM) stores weights as capacitance,eliminating DC sneak paths and IR‐drop, yielding near‐zero standbypower. In this perspective, we present a device to systems level performance analysis of most promising architectures and predict apathway for upscaling capacitive CIM for sustainable edge computing ...
Kapil Bhardwaj +2 more
wiley +1 more source
Quantization for feedback control and estimation [PDF]
2008 27th Chinese Control Conference, 2008 This paper discusses a number of technical issues in a new area of research in control systems, namely, quantized feedback control and estimation. This area is motivated by the increasing need of incorporating communication networks in a control system.
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Advanced Intelligent Systems, EarlyView.A piezoelectric meta‐transducer generates an ultrasonic rainbow, steering guided elastic waves to different angles according to frequency. A dithering‐based binary electrode design enables a closer realization of the target wavenumber filter, improving directional purity and suppressing unwanted lobes. Numerical and experimental validation demonstrates
Masoud Mohammadgholiha +5 more
wiley +1 more source
Chaotic Quantized Feedback Stabilizers: The Scalar Case [PDF]
Communications in Information and Systems, 2004 In this paper we consider practical stabilization strategies of scalar linear systems by means of quantized feedback maps which use a minimal number of quantization levels. These stabilization schemes are based on the chaotic properties of piecewise affine maps and their perfor- mance can be analyzed in terms of the mean time needed to shrink the ...
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Advanced Intelligent Systems, EarlyView.This work presents a bio‐inspired computing framework for Parkinson's disease analog recognition using electroencephalogram signals. Temporally encoded EEG features stimulate a mycelium‐inspired memristive reservoir, where disease‐related patterns emerge through physical spatiotemporal dynamics.
Ioannis K. Chatzipaschalis +5 more
wiley +1 more source
Signature Quantization in Fading CDMA with Limited Feedback [PDF]
IEEE Transactions on Communications, 2011 In this work, we analyze the performance of a signature quantization scheme for reverse-link Direct Sequence (DS)- Code Division Multiple Access (CDMA). Assuming perfect estimates of the channel and interference covariance, the receiver selects the signature that minimizes interference power or maximizes signal-to-interference plus noise ratio (SINR ...
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Time‐Delayed Spiking Reservoir Computing Enables Efficient Time Series Prediction
Advanced Intelligent Systems, EarlyView.This study proposes time‐delayed spiking reservoir computing (TDSRC) for efficient time series prediction. By concatenating time‐lagged states, TDSRC constructs an expanded readout feature vector without altering internal reservoir dynamics. This approach enables highly accurate forecasting with significantly fewer neurons, providing a resource ...
Pin Jin +3 more
wiley +1 more source