Suchada Sitjongsataporn

A Mixed-Tone RLS algorithm with orthogonal projection for Per-Tone DMT equalisation

A methodology of mixed-tone recursive least squares algorithm development based on an orthogonal projection approach is presented for per-tone equalisation in discrete multitone systems. A mixed-tone cost function described as the sum of weight-estimated errors is minimised to achieve the solutions for different per-tone equalisers simultaneously. Simulation results reveal improvement of achievable bit rate and signal to noise ratio performance as compared to the PTEQ exploiting conventional RLS algorithm.

An Adaptive Step-size Order Statistic Time Domain Equaliser for Discrete Multitone Systems

In this paper, an adaptive step-size order statistic time domain equaliser (TEQ) for discrete multitone (DMT) systems is presented. The authors have shown that the TEQ and target impulse response (TIR) solutions of a costly constrained optimisation can be cheaply obtained by means of a variant of the well-known low-complexity normalised least mean square (NLMS) algorithm. An algorithm for adapting step-size of an order statistic NLMS TEQ is presented. Simulation results reveal that the trajectories of step-size parameters of the proposed algorithm converge to their own equilibria despite large variations in initial step-size settings. Robustness of proposed TEQ with different types of disturbations such as additive white Gaussian noise (AWGN) and near-end crosstalk (NEXT) is also shown as a comparison with the existing minimum mean square error-TEQ (MMSE-TEQ)

Video shot boundary detection based on candidate segment selection and transition pattern analysis

Video shot boundary detection or shot segmentation is an integral part of semantic video analysis. The objective of this process is to automatically detect the boundary region in video that further segment the video into meaningful shot, scene and so on. Video frame feature representation therefore plays an important role in the process where it directly affects the overall performance of the system. The transition points between meaningful scenes can be emphasised by the extracted features. In this paper, a combination of global and local feature descriptors is implemented to represent the temporal characteristic in video. Motivated by computational efficiency and practical implementation, a video shot boundary detection scheme using adaptive thresholding is proposed. Candidate segment selection and transition pattern analysis are implemented by the dissimilarity score between video frames. The performance evaluation is constructed on a golf video dataset using the precision and recall performance measures.

A high speed low input current low voltage CMOS current comparator

A new high speed low input current comparator is proposed in this paper. Based on a simple negative feedback scheme around the transimpedance stage, with an emphasis on a very large loop-gain, the transformed voltage signal is maintained at the lowest swing that results in a speed improvement. On a 0.25 /spl mu/m TSMC CMOS process, simulation results demonstrate propagation delays of. 3.6 ns with /spl plusmn/100 nA input current and 1.5 Volts power supply, while the smallest input current is /spl plusmn/50 pA. Performances are also shown with other V/sub DD/ such as 1.0 and 1.8 Volts.

Multi-Modal Visual Features-Based Video Shot Boundary Detection

One of the essential pre-processing steps of semantic video analysis is the video shot boundary detection (SBD). It is the primary step to segment the sequence of video frames into shots. Many SBD systems using supervised learning have been proposed for years; however, the training process still remains its principal limitation. In this paper, a multi-modal visual features-based SBD framework is employed that aims to analyze the behaviors of visual representation in terms of the discontinuity signal. We adopt a candidate segment selection that performs without the threshold calculation but uses the cumulative moving average of the discontinuity signal to identify the position of shot boundaries and neglect the non-boundary video frames. The transition detection is structurally performed to distinguish candidate segment into a cut transition and a gradual transition, including fade in/out and logo occurrence. Experimental results are evaluated using the golf video clips and the TREC2001 documentary video data set. Results show that the proposed SBD framework can achieve good accuracy in both types of video data set compared with other proposed SBD methods.

Low complexity adaptive step-size filtered gradient-based per-tone DMT equalisation

In this paper, a low complexity adaptive step-size filtered gradient-based scheme for per-tone equalisation is investigated for discrete multitone systems. A variant of the filtered gradient adaptive algorithms has been presented in literature for the normalised version of the orthogonal gradient adaptive algorithm which employs the mixed-tone exponentially weighted least squares criterion. A low complexity adaptive step-size approach is proposed by exploiting an estimate of autocorrelation between previous and present weight-estimated error to control step-size update. In order to ensure good tracking and convergence speed, the step-size is adjusted recursively for different per-tone equalisers. Simulation results show that the trajectories of step-size of the proposed algorithm converge to its own equilibrium despite large variations in initial step-size settings. The proposed algorithm achieves superior performance, faster convergence rate and lower computational complexity than the existing algorithms.

Mixed-tone normalised orthogonal gradient adaptive per-tone DMT equalisation

A mixed-tone normalised orthogonal gradient adaptive algorithm is introduced for per-tone equalisation in discrete multitone systems. We describe briefly about the normalised orthogonal gradient adaptive algorithm that is formulated from the filtered gradient adaptive algorithm by introducing an orthogonal constraint between the direction vectors. By means of the mixed-tone cost function, the sum of weight-estimated errors is minimised in order to achieve the solutions for different per-tone equalisers. Simulation results reveal that bit rate performance can be improved in comparison with the existing recursive least squares algorithm.

Bit rate maximising per-tone equalisation with adaptive implementation for DMT-based systems

We present a bit rate maximising per-tone equalisation (BM-PTEQ) cost function that is based on an exact subchannel SNR as a function of per-tone equaliser in discrete multitone (DMT) systems. We then introduce the proposed BM-PTEQ criterion whose derivation for solution is shown to inherit from the methodology of the existing bit rate maximising time-domain equalisation (BM-TEQ). By solving a nonlinear BM-PTEQ cost function, an adaptive BM-PTEQ approach based on a recursive Levenberg-Marquardt (RLM) algorithm is presented with the adaptive inverse square-root (iQR) algorithm for DMT-based systems. Simulation results confirm that the performance of the proposed adaptive iQR RLM-based BM-PTEQ converges close to the performance of the proposed BM-PTEQ. Moreover, the performance of both these proposed BM-PTEQ algorithms is improved as compared with the BM-TEQ.

Abrupt shot boundary detection based on averaged two-dependence estimators learning

Video shot boundary detection is the process of automatically detecting the meaningful boundary in video data. It becomes an essential pre-processing step to video analysis, summarisation and other content-based retrieval. Video frame feature representation also plays an important role in the process where it directly affects to the performance of the system. Histogram dissimilarity-based with the pre-processed features scheme are proposed to represent the temporal characteristic in videos. Motivated by the practical applications with moderate computational time, supervised abrupt shot boundary detection with averaged two-dependence estimators probabilistic classification learning scheme is proposed in this paper. The performance evaluation is performed by TRECVID 2007 videos dataset containing various types of video category. The performance of the proposed scheme can be expressed in terms of precision and recall to detect the correct abrupt video shot.

Recursive Levenberg-Marquardt Per-Tone Equalisation for Discrete Multitone systems

Recursive Levenberg-Marquardt (RLM) algorithm is presented for per-tone equalisers in discrete multitone systems. We introduce how to formulate the proposed RLM algorithm for non-linear adaptive filter. Simulation results show that the proposed RLM algorithm can improve bit rate performance and Signal to Noise Ratio improvement as compared to the existing recursive least squares-based algorithms and matched filter bound.