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In this article the approximation capability of the extreme learning machine is studied. Specifically the impact of the range from which the input weights and biases are randomly generated on the fitted curve complexity is analyzed. The guidance for how to generate the input weights and biases to get good performance in approximation of the functions of one variable is provided.
Active Noise Canceller has become very common in modern day to day electronic equipment. The adaptive filters installed inside this canceller play a crucial role in noise cancellation. The computational complexity as well as the structural complexity of the filter is an important factor to be considered for the overall performance. This depends on the structure of the filter. The structure depends...
The development of wireless communications created broad opportunities in mobile communications. However, poor channel estimation and lack of proper Doppler shift compensation techniques limit the mobility considerably. Therefore, a high quality and low-complexity channel estimation is one of the most important conditions for high mobility. In this paper we propose a low-complexity delay-Doppler search...
Noise cancellation is very important step for ECG signal processing. For this problem, there are many methods had been applied. For example, Wavelet based de-noises, EMD based de-noise, Kalman based de-noise, etc. for resource very limited system, the above method may be not fit into the system resource. Algorithm complexity and resource requirement will be the major concern in this work. In this...
In this paper we demonstrate a new density based clustering technique, CODSAS, for online clustering of streaming data into arbitrary shaped clusters. CODAS is a two stage process using a simple local density to initiate micro-clusters which are then combined into clusters. Memory efficiency is gained by not storing or re-using any data. Computational efficiency is gained by using hyper-spherical...
We consider change-point estimation in a sequence of high-dimensional signals given noisy observations. Classical approaches to this problem such as the filtered derivative method are useful for sequences of scalar-valued signals, but they have undesirable scaling behavior in the high-dimensional setting. However, many high-dimensional signals encountered in practice frequently possess latent low-dimensional...
Cognitive radio is an emerging wireless technology that is capable of efficiently coordinating the use of the currently scarce spectrum resources, and spectrum sensing constitutes its most crucial operation. This paper proposes wideband multichannel spectrum sensing methods utilizing fast Fourier transform or filter-bank-based methods for spectrum analysis. Fine-grained spectrum analysis facilitates...
We study stability and uniqueness for the phase retrieval problem. That is, we ask when is a signal x ε Rn stably and uniquely determined (up to small perturbations), when one performs phaseless measurements of the form yi = |aTix|2 (for i = 1,…, N), where the vectors ai ε Rn are chosen independently at random, with each coordinate aij ε R being chosen independently from a fixed sub-Gaussian distribution...
A pole-projection approach is proposed as a useful tool for multi-objective robust control design. Different load conditions or nonlinearities are considered in the design by simultaneously stabilizing a set of linear models. The idea is to repeatedly project the poles for each model (one at a time) to a generalized stability region until all models are stabilized. Similarly, pole projections are...
A method of incorporating implementation aspects in the algorithm-level design of nonlinear filters is proposed. As a case study, the trade-off between the visual properties and the complexity of soft morphological filters is studied using training-based optimization methods. Specifically, it is shown that the use of the complexity constraints can provide the filter designer valuable information on...
The present paper presents a source separation algorithm used for noise suppression. The complexity of the algorithm at hand is treated. A reformulation of the algorithm reduces the number of arithmetic operation by a factor of five. Measurement noise is discussed and remedies are suggested and presented in simulations. An alternative estimation of correlations is suggested which might be more suited...
The recently proposed LCL-PTV structures for narrowband interference suppression in DS/SS systems are examined and compared in terms of output SIR. New LCL-PTV prediction/subtraction filters are proposed, which are shown to provide the same SIR performances of the LCL-PTV whitening structures, with the additional advantage of being amenable to blind adaptive implementation. Simulation results are...
This paper examines the application of nonlinear signal processing techniques to the development of adaptive equalisers for frequency domain multiple access (FDMA) and multi-user detectors for code division multiple access (CDMA). Current issues are discussed and key problems identified.
In this paper the detection of Trellis Coded Modulated signals corrupted by Intersymbol Interference, Co-Channel Interference and nonlinear impairments is treated as a classification task by means of a Clustering Based Sequence Equalizer-Decoder. The receiver performs jointly decoding and equalization of trellis encoded signals. No specific model is required for the channel or for the interference...
The need for decomposing a signal into its optimal representation arises in many applications. In such applications, one can usually represent the signal as a combination of an over-complete dictionary elements. The non-uniqueness of signal representation, in such dictionaries, provides us with the opportunity to adapt the signal representation to the signal. The adaptation is based on sparsity, resolution...
Power-line communications (PLC) commonly employs orthogonal frequency-division multiplexing (OFDM) as the modulation technique, and impulsive noise has a significant negative impact on its performance. Using the property of null subcarriers in OFDM and the fact that impulsive noise is sparse, we formulate a minimization problem to detect and estimate the impulsive noise. In previous works, ℓ1-norm...
We study the problem of actively learning a multi-index function of the form f(x) = g0(A0x) from its point evaluations, where A0 ∈ ℝk×d with k ≫ d. We build on the assumptions and techniques of an existing approach based on low-rank matrix recovery (Tyagi and Cevher, 2012). Specifically, by introducing an additional self- concordant like assumption on g0 and adapting the sampling scheme and its analysis...
This paper investigates the variable tap-length algorithm for structure adaptation. Among existing algorithms, the Segmented Filter (SF) and Gradient Descent (GD) algorithms are of interest as both can track the tap-length variations quickly. In this paper, we first compare the SF and GD algorithms and show that each has advantages/disadvanges relative to the other. Then we propose an improved variable...
In this paper we study the use of lattice decoders in the reception of layered vertical space-time codes with square constellations. We rewrite the vertical code reception problem to make it amenable to lattice decoding. We compare the complexity and probability of error of lattice decoding with those of V-BLAST. Several properties of the behavior of lattice decoders that will have a definite impact...
A reduced complexity normalized least-mean-square (NLMS) algorithm is presented for blind linear adaptive multiuser detection in synchronous direct-sequence CDMA systems. Selective partial updating is employed to reduce the computational complexity of the NLMS algorithm. The basic idea behind selective partial updating is to update only a small number of the adaptive filter coefficients at each iteration...
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