Mohd Zuki Yusoff

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A time domain constrained subspace-based estimator for extracting a visual evoked potential (VEP) from a highly noisy brain activity is proposed. Generally, the desired VEP is corrupted by background electroencephalogram (EEG) behaving as colored noise, making the overall signal-to-noise ratio as low as -10 dB. The estimator is designed to minimize signal(More)
A signal subspace approach for extracting visual evoked potentials (VEPs) from the background electroencephalogram (EEG) colored noise without the need for a prewhitening stage is proposed. Linear estimation of the clean signal is performed by minimizing signal distortion while maintaining the residual noise energy below some given threshold. The(More)
A "single-trial" signal subspace approach for extracting visual evoked potential (VEP) from the ongoing 'colored' electroencephalogram (EEG) noise is proposed. The algorithm applies the generalized eigendecomposition on the covariance matrices of the VEP and noise to transform them jointly into diagonal matrices in order to avoid a pre-whitening stage. The(More)
Estimating a visual evoked potential (VEP) from the human brain is challenging since its signal-to-noise ratio (SNR) is generally very low. An eigendecomposition-based subspace approach originally proposed for enhancing speech corrupted by colored noise, has been investigated and tested in the single trial extraction of VEPs. This scheme arbitrarily labeled(More)
Estimating a visual evoked potential (VEP) from the human brain is challenging since its signal-to-noise ratio (SNR) is generally very low. An optimization and eigen-decompositionbased subspace approach has been investigated and tested to estimate the latencies of visual evoked potential (VEP) signals which are highly corrupted by spontaneous(More)
In this paper, we propose a road sign detection and recognition algorithm for an embedded application. The algorithm is based on the Hough transform method to detect lines in order to identify and determine the shape of the road sign. Shape measurements are currently employed to identify the road sign ratios of area and perimeter. The variables are compared(More)
The demand for high data rate and channel bandwidth is always the primary area of concern in modern wireless communication systems. All the modern wireless communication system applications are rapidly shifting towards multiple input multiple output (MIMO) from single input and single output (SISO) and single input multiple output (SIMO) systems, increasing(More)
This paper develops a feature-based Automatic Modulation Classification (AMC) algorithm for spatially multiplexed Multiple-Input Multiple-Output (MIMO) systems. The proposed algorithm employs two Higher Order Cumulants (HOCs) of the estimated transmit signal streams as discriminating features, and a multiclass Support Vector Machine (SVM) as a(More)
In this paper, we propose a road sign detection and recognition algorithm for an embedded application, which requires computationally simple but accurate algorithms. The algorithm is developed by using the Hue Saturation Intensity (HSI) color space to segment the road signs color (red, yellow, blue and white) and the regions of interest (ROI) in order to(More)