H.M.D. Ip

Imperial College London, London, ENG, United Kingdom

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Publications (9)4.48 Total impact

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    ABSTRACT: Using a modified version of the linear cellular neural network (CNN) filtering paradigm recently proposed by the authors, we designed a nonseparable spatiotemporal bandpass filter with tunable spatiotemporal passband volumes. The filter presented here qualitatively resembles spatiotemporal receptive field models for the primary visual cortex. Numerical simulation results confirm the bandpass characteristic of our filtering network.
    Circuits and Systems, 2008. ISCAS 2008. IEEE International Symposium on; 06/2008
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    ABSTRACT: Linear cellular neural networks (CNNs) are capable of performing efficient spatiotemporal filtering operations as recursive infinite impulse response (IIR) filters. Particularly, linear CNNs can be characterized as a spatial frequency-dependent recursive temporal filter with complex coefficients. Based on a modified version of the CNN paradigm recently proposed by the authors, nonseparable spatiotemporal bandpass filters with tunable spatiotemporal passband volumes are synthesized. The filters reported here qualitatively resemble spatiotemporal receptive field models for the primary visual cortex. Numerical simulation results confirm the bandpass characteristics of our filtering network.
    Circuits and Systems I: Regular Papers, IEEE Transactions on 03/2008; · 2.24 Impact Factor
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    ABSTRACT: In this paper, we extend the linear cellular neural network (CNN) paradigm by introducing temporal derivative diffusion connections between neighboring cells. Our proposal results in an analog network topology for implementing general continuous-time discrete-space mixed-domain 3-D rational transfer functions for linear filtering. The network connections correspond one-to-one to the transfer function coefficients. The mixed-domain frequency response is treated as a temporal frequency-dependent spatial function and we show how nonseparable properties of the spatio-temporal magnitude response can be derived from the combination of: 1) sinusoidal functions of spatial frequencies and 2) polynomials of the continuous-time frequency in the 3-D frequency response expression. A generic VLSI-compatible implementation of the network based on continuous-time integrators is also proposed. Based on our proposed CNN extension, the analysis of a spatio-temporal filtering example originated from analytical modeling of receptive fields of the visual cortex is presented and a spatio-temporal cone filter is designed and presented with numerical simulation results.
    Circuits and Systems I: Regular Papers, IEEE Transactions on 03/2008; · 2.24 Impact Factor
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    ABSTRACT: This paper outlines the design and simulated performance of a novel, current-mode, companding, Class-AB, Sinh lossy integrator. Prior Sinh filter designs utilize current conveyor-like blocks which incorporate both N- and P-type devices in alternate cascode arrangement to process the split-ted phases of the input. However, if these blocks were to be designed in weak inversion CMOS, the bulks of all the devices involved should be connected to their respective sources for accurate exponential/logarithmic conformity, which dictates the use of a triple-well process. Triple-well processes, apart from the fact that are not always available, have increased parasitics compared to twin-well ones, making the design and optimization of these already complicated filters a rather difficult one. In this paper, we present a new Sinh lossy integrator circuit that uses (either N- or) P-type devices rendering it to be practically realizable in any standard twin-well process. The circuit has been designed in 0.35mum AMS CMOS process with all simulation results obtained from Cadence Design Frameworkreg. The resulting lossy integrator exhibits a simulated input dynamic range greater than 120dB with only one integrating capacitor, while dissipating 0.3muW of power.
    Circuits and Systems, 2007. ISCAS 2007. IEEE International Symposium on; 06/2007
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    ABSTRACT: This paper details the design and operation of a two-stage current-input current-output topology suitable for three-electrode amperometric sensor measurements. The first stage is an interface providing current-follower block, whereas the second stage is a novel hyperbolic-sine-based current amplification stage. The linear amplification stage bases its operation upon the compressive sinh-1 conversion of the interfaced current to an intermediate auxiliary voltage and the subsequent sinh expansion of the same voltage. The proposed topology has been simulated using the parameters of the commercially available 0.8 mum AMS CMOS process. A variety of confirming cadence design framework simulation results for current gain values ranging from 10 to 1000 are provided. The proposed interfacing/amplification architecture operates in weak-inversion consuming 0.11-5.5 muWs and occupies an area of 900 x 500 mum2.
    01/2007;
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    ABSTRACT: We report the development of a new CNN based theoretical framework and its on-going analog VLSI implementation for continuous-time discrete-space spatiotemporal filtering. Our proposed formulation, which stems from the theory of linear cellular neural networks, is capable of realizing a wide range of linear spatiotemporal dynamics. Based on our proposed framework, 3D nonseparable spatiotemporal filters are synthesized. The filters are presented in the form of continuous-time/discrete-space mixed domain transfer functions with responses qualitatively resembling visual cortical bandpass spatiotemporal receptive fields. Analog VLSI building blocks suitable for the implementation of the required spatiotemporal dynamics are presented. Simulation results on AMS 0.35mum process parameters of a 5times5 array, with electrical parameters tuned to realize the spatiotemporal dynamics of one of our synthesized 3D bandpass filters, are presented
    Cellular Neural Networks and Their Applications, 2006. CNNA '06. 10th International Workshop on; 09/2006
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    ABSTRACT: This work presents the use of a two-layered recursive network to produce biomimetic visual spatiotemporal bandpass receptive fields. Simulation results of the transistor network based on an array of spatially coupled polyphase Gm-C filters are also included. Our bioinspired approach captures the essence of efficient processing in recursive cortical networks and at the same time backed by the vigorous analytical tools found in cellular neural network theory within the CAS community.
    Biomedical Circuits and Systems Conference, 2006. BioCAS 2006. IEEE; 01/2006
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    ABSTRACT: An analog network topology suitable for implementing continuous-time/discrete-space mixed domain rational spatiotemporal transfer functions is proposed. We also provide a generic VLSI-compatible implementation of the network based on continuous-time integrators. Numerical simulation results confirm the expected operation of a network realizing a first order velocity selective filter.
    Circuits and Systems, 2005. ISCAS 2005. IEEE International Symposium on; 06/2005
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    ABSTRACT: Oriented two dimensional spatial low-pass filters are useful for image processing tasks such as adaptive smoothing. We propose an oriented low-pass filter suitable for CNN implementations. The filter design procedure starts with an oriented Gaussian filter with the final CNN implementation involves only five non-zero coefficients in its feedback template, but achieving both orientation and scale tunable responses. By elaborating on the existing linear CNN stability criterion in terms of multidimensional signals theory, the stability of our CNN filter is also analyzed. Simulation results confirm the spatial impulse response of the CNN is indeed orientation and scale tunable.
    Circuits and Systems, 2005. 48th Midwest Symposium on; 01/2005