By Topic

Signal Processing, IET

Issue 3 • Date May 2009

Filter Results

Displaying Results 1 - 6 of 6
  • A successive termination and elimination method for fast H.264/AVC SATD-based inter mode decision

    Page(s): 165 - 176
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (565 KB)  

    A successive termination and elimination (STE) method to achieve fast inter mode decision is proposed. The termination detection starts from residual homogeneous detection and then spatial homogeneous detection is performed for each 16 times 16 macroblock. For either the residual or spatial homogeneous case, the authors can directly terminate the inter prediction and choose the 16 times 16 mode as the best inter mode. For non-homogeneous cases, the authors then carry out the 8 times 8 subblock motion estimation. Based on the cost analyses of the 8times8 and 16 times 16 modes, the elimination detection method, which could help to remove unlikely 8 times 16 and 16 times 8 modes, is also suggested. Similarly, the STE method for each 8times8 block can also be applied to decide if the inter prediction needs to be further performed for smaller subblocks. Once the algorithm reaches the termination stage, the best inter mode will be decided by selecting the least cost among all searched modes. Experimental results reveal that the proposed STE method can save about 56% of coding time in inter prediction with a slight performance degradation compared with the original method proposed by JM10.1 and outperforms some existing methods in both coding performance and coding time. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Target tracking with two passive infrared non-imaging sensors

    Page(s): 177 - 188
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (312 KB)  

    A new solution for target tracking in air space with two infrared (IR) sensors is presented. The principle of triangulation is used as a basic method for range estimation. However, when the target directions are nearly collinear relative to the baseline, this method produces unacceptable results. The problem is solved by introducing the ratio of IR energy adsorbed at the end of a baseline in a measurement vector within the extended Kalman filter type target state estimator. Also, a recursive estimator for the extinction coefficient that describes the influence of the atmosphere is designed. This combination results in a new adaptive structure for simultaneous estimation of target kinematic states and atmospheric parameters. Such a structure performs much better than the standard triangulation method, yielding acceptable results even in the case where target directions are close to the baseline. Simulation and experimental results demonstrate the feasibility and limitations of the proposed approach. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Multiple frame size and rate analysis for speaker recognition under limited data condition

    Page(s): 189 - 204
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (311 KB)  

    This work demonstrates the usefulness of multiple frame size and rate (MFSR) analysis for speaker recognition under limited data condition. Present day speaker recognition systems assume the availability of sufficient data for modelling and testing. Owing to this, speech signals are analysed with fixed frame size and rate, which may be termed as single frame size and rate (SFSR) analysis. In the limited data condition available training and testing data is small. If we use SFSR analysis, then it may not provide sufficient feature vectors to train and test the speaker. Further, insufficient feature vectors lead to poor speaker modelling during training and may not yield reliable decision during testing. As part of analysis, we demonstrate the use of multiple frame size (MFS), multiple frame rate (MFR) and MFSR analysis techniques for speaker recognition under limited data condition. These techniques are specifically useful to mitigate the sparseness of limited feature vectors during training and testing. These techniques produce relatively more number of feature vectors. This helps in better modelling and testing under limited data conditions. The experimental results show that use of MFS, MFR and MFSR analysis improves the performance significantly compared to SFSR analysis. The MFSR analysis even outperforms the Gaussian mixture model-universal background model (GMM-UBM) performance, the most widely used modelling technique. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Statistical model-based voice activity detection using support vector machine

    Page(s): 205 - 210
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (433 KB)  

    From an investigation of a statistical model-based voice activity detection (VAD), it is discovered that a simple heuristic way like a geometric mean has been adopted for a decision rule based on the likelihood ratio (LR) test. For a successful VAD operation, the authors first review the behaviour mechanism of support vector machine (SVM) and then propose a novel technique, which employs the decision function of SVM using the LRs, while the conventional techniques perform VAD comparing the geometric mean of the LRs with a given threshold value. The proposed SVM-based VAD is compared to the conventional statistical model-based scheme, and shows better performances in various noise environments. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Design of non-uniform filter bank transmultiplexer with canonical signed digit filter coefficients

    Page(s): 211 - 220
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (436 KB)  

    Design of non-uniform filter bank transmultiplexer (NUFB TMUX) with canonical signed digit (CSD) coefficients is presented. NUFB TMUX is preferred in a multicarrier communication system when applications with different data rates are to be multiplexed. If the filter coefficients are represented in CSD format, the hardware complexity of the NUFB TMUX can be reduced. A continuous coefficient NUFB TMUX is designed and the coefficients of the filters are synthesised in CSD format using genetic algorithm (GA). Separate objective functions are formulated for the fitness evaluation of the filters. Chromosomes are encoded as ternary digit strings. New crossover and mutation techniques are introduced to preserve the canonical property of the signed power of two (SPT) representations. For the fast convergence of the GA, position-dependent probability of mutation is used. Simulation results show that the CSD coefficient NUFB TMUX designed using the proposed algorithm has better signal-to-interference ratio (SIR) than that of continuous coefficient NUFB TMUX and CSD coefficient NUFB TMUX obtained by rounding. Frequency responses of its filters are better than that of the filters in CSD coefficient NUFB TMUX obtained by rounding and comparable with that of continuous coefficient NUFB TMUX. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Unitary spherical esprit: 2-d angle estimation with spherical arrays for scalar fields

    Page(s): 221 - 231
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (659 KB)  

    The authors consider the problem of two-dimensional (2-D) direction-of-arrival estimation of multiple plane waves incident on a spherical array. We propose a novel subspace technique that provides automatically paired source azimuth and elevation estimates relying on a spherical phase-mode excitation approach. The algorithm is remarkable for the low computational complexity and enhanced performance in correlated source scenarios by relying on a real beamspace approach, which allows forward-backward averaging. Moreover, the technique yields very accurate estimates by including spherical phase modes of different orders. This is demonstrated by comparing the mean error of the angle estimates obtained by spherical ESPRIT and the corresponding Cramer Rao bounds. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.

Aims & Scope

IET Signal Processing publishes novel contributions in signal processing.

Full Aims & Scope

Meet Our Editors

IET Research Journals
iet_spr@theiet.org