Scale-Invariant Feature Transform (SIFT) has lately attracted attention in computer vision as a robust keypoint detection algorithm which is invariant for scale, rotation and illumination changes. However, its computational complexity is too high to apply in practical real-time applications. This paper proposes a low complexity keypoint extraction algorithm based on SIFT descriptor and utilization of the database, and its real-time hardware implementation for Full-HD resolution video. The proposed algorithm computes SIFT descriptor on the keypoint obtained by corner detection and selects a scale from the database. It is possible to parallelize the keypoint detection and descriptor computation modules in the hardware. These modules do not depend on each other in the proposed algorithm in contrast with SIFT that computes a scale. The processing time of descriptor computation in this hardware is independent of the number of keypoints because its descriptor generation is pipelining structure of pixel. Evaluation results show that the proposed algorithm on software is 12 times faster than SIFT. Moreover, the proposed hardware on FPGA is 427 times faster than SIFT and 61 times faster than the proposed algorithm on software. The proposed hardware performs keypoint extraction and matching at 60 fps for Full-HD video.

Wireless sensor nodes are becoming more and more common in various settings and require a long battery life for better maintainability. Since most sensor nodes are powered by batteries, energy efficiency is a critical problem. In an experiment, we observed that when peak power consumption is high, battery voltage drops quickly, and the sensor stops working even though some useful charge remains in the battery. We propose three off-line algorithms that extend battery life by scheduling sensors' execution time that is able to reduce peak power consumption as much as possible under a deadline constraint. We also developed a simulator to evaluate the effectiveness of these algorithms. The simulation results showed that one of the three algorithms dramatically can extend battery life approximately three time as long as in simultaneous sensor activation.

In this paper we propose a method to use features of an individual object to locate and recognize this object concurrently in a static image with Multi-feature fusion based on multiple objects sample library. This method is proposed based on the observation that lots of previous works focuses on category recognition and takes advantage of common characters of special category to detect the existence of it. However, these algorithms cease to be effective if we search existence of individual objects instead of categories in complex background. To solve this problem, we abandon the concept of category and propose an effective way to use directly features of an individual object as clues to detection and recognition. In our system, we import multi-feature fusion method based on colour histogram and prominent SIFT (p-SIFT) feature to improve detection and recognition accuracy rate. p-SIFT feature is an improved SIFT feature acquired by further feature extraction of correlation information based on Feature Matrix aiming at low computation complexity with good matching rate that is proposed by ourselves. In process of detecting object, we abandon conventional methods and instead take full use of multi-feature to start with a simple but effective way-using colour feature to reduce amounts of patches of interest (POI). Our method is evaluated on several publicly available datasets including Pascal VOC 2005 dataset, Objects101 and datasets provided by Achanta et al.

Wireless personal area networks (WPANs) will play an important role in next-generation communication networks. Currently, two technologies are being considered for the physical layer of WPANs, based on the two ultra wideband (UWB) standards, namely, multiband orthogonal frequency division multiplexing (MB-OFDM) UWB and direct-sequence (DS) UWB. The coexistence issue of these two types of WPANs in the same coverage area, raises new issues and introduces new problems which should be dealt with to avoid performance degradation. In particular, efficient radio resource management (RRM) in such environments is challenging. Indeed, the coexistence of heterogenous UWB based WPANs (UPANs) has an ad hoc nature, which requires RRM approaches that are different from traditional infrastructure-based ones. In this paper, we propose new algorithms for two RRM modules in heterogeneous UPANs, namely, radio access technology (RAT) selection and vertical handoff (VHO). To improve the overall performance of the system, our design considers possible narrowband interference (NBI) in the environment as well as the link outage probability, in the decision process. We also provide an analytical model based on a 4D Markov process to study the system in equilibrium and derive the performance metrics, namely, the new-call and handoff-call blocking probabilities, throughput and average carried traffic. Numerical results and comparisons show that our design achieves enhanced performance in terms of throughput and grade of service (GoS).

Substrate coupling of radio frequency (RF) components is represented by equivalent circuits unifying a resistive mesh network with lumped capacitors in connection with the backside of device models. Two-port S-parameter test structures are used to characterize the strength of substrate coupling of resistors, capacitors, inductors, and MOSFETs in a 65 nm CMOS technology with different geometries and dimensions. The consistency is finely demonstrated between simulation with the equivalent circuits and measurements of the test structures, with the deviation of typically less than 3 dB for passive and 6 dB for active components, in the transmission properties for the frequency range of interest up to 8 GHz.

A rectangular drawing is a plane drawing of a graph in which every face is a rectangle. Rectangular drawings have an application for floorplans, which may have a huge number of faces, so compact code to store the drawings is desired. The most compact code for rectangular drawings needs at most 4f-4 bits, where f is the number of inner faces of the drawing. The code stores only the graph structure of rectangular drawings, so the length of each edge is not encoded. A grid rectangular drawing is a rectangular drawing in which each vertex has integer coordinates. To store grid rectangular drawings, we need to store some information for lengths or coordinates. One can store a grid rectangular drawing by the code for rectangular drawings and the width and height of each inner face. Such a code needs 4f-4 + f⌈log W⌉ + f⌈log H⌉ + o(f) + o(W) + o(H) bits*, where W and H are the maximum width and the maximum height of inner faces, respectively. In this paper we design a simple and compact code for grid rectangular drawings. The code needs 4f-4 + (f+1)⌈log L⌉ + o(f) + o(L) bits for each grid rectangular drawing, where L is the maximum length of edges in the drawing. Note that L ≤ max{W,H} holds. Our encoding and decoding algorithms run in O(f) time.

In recent years, heterogeneous cellular network (HetNet) topology has been attracting much attention. HetNet, which is a network topology with low power base stations installed inside the cell range of conventional macrocells, can realize network capacity enhancement through the effects of macrocell offloading and cell shrinkage. Due to the heterogeneity nature of HetNet, network designers should carefully consider about the interference management, resource allocation, user association and cell range expansion. These issues have been well studied in recent literatures. However, one of the important problems which has not been well investigated in conventional works is the base station (BS) deployment problem in HetNet. This paper investigates the optimal pico base station deployment in heterogeneous cellular networks especially with the existence of hotspots. In this paper, pico BS locations are optimized together with other network parameters including spectrum splitting ratio and signal-to-interference-noise ratio (SINR) bias for cell range expansion to maximize the total system rate, by considering two spectrum allocation strategies, i.e. spectrum overlapping and spectrum splitting. Numerical results show that the optimized pico BS locations can improve the system rate, the average user rate and outage user rate in HetNet with hotspots.

In this paper, we propose four different strategies of node pair selection in multiple input multiple output (MIMO) interference channel where interference alignment (IA) is considered as a transceiver design method. In the first scheme, we consider the maximization of the sum rate by selecting node pairs in a brute force way. We also propose a sub-optimal sum rate maximization scheme with lower complexity than the first scheme. In the third scheme, we aim to minimize the number of links among pairs which incurs the outage in MIMO interference channel. In the fourth scheme, we suggest a max-min node pair selection scheme to enhance both the sum rate and the outage probability. Simulation results demonstrate that all our proposed node pair selection schemes can increase the sum rate but also while also reducing the outage probability compared to the scheme with random node pair selection.

Dichotomous coordinate descent (DCD) iterations method has been proposed for adaptive feedback cancellation, which uses a fixed number of iterations and a fixed amplitude range. In this paper, improved DCD algorithms are proposed, which substitute the constant number of iterations and the amplitude range with a variable number of iterations(VI) and/or a variable amplitude range(VA). Thus VI-DCD, VA-DCD and VIA-DCD algorithms are obtained. Computer simulations are used to compare the performance of the proposed algorithms against original DCD algorithm, and simulation results demonstrate that significant improvements are achieved in the convergence speed and accuracy. Another notable conclusion by further simulations is that the proposed algorithms achieve superior performance with a real speech segment as the input.

Pulse coupled neural network (PCNN) is a new type of artificial neural network specific for image processing applications. It is a single layer, two dimensional network with neurons which have 1:1 correspondence to the pixels of an input image. It is convenient to process the intensities and spatial locations of image pixels simultaneously by applying a PCNN. Therefore, we propose a modified PCNN with anisotropic synaptic weight matrix for image edge detection from the aspect of intensity similarities of pixels to their neighborhoods. By applying the anisotropic synaptic weight matrix, the interconnections are only established between the central neuron and the neighboring neurons corresponding to pixels with similar intensity values in a 3 by 3 neighborhood. Neurons corresponding to edge pixels and non-edge pixels will receive different input signal from the neighboring neurons. By setting appropriate threshold conditions, image step edges can be detected effectively. Comparing with conventional PCNN based edge detection methods, the proposed modified PCNN is much easier to control, and the optimal result can be achieved instantly after all neurons pulsed. Furthermore, the proposed method is shown to be able to distinguish the isolated pixels from step edge pixels better than derivative edge detectors.

This paper describes algorithms for generating low intermodulation-distortion (IMD) two-tone sinewaves, for such as communication application ADC testing, using an arbitrary waveform generator (AWG) or a multi-bit ΣΔ DAC inside an SoC. The nonlinearity of the DAC generates distortion components, and we propose here eight methods to precompensate for the IMD using DSP algorithms and produce low-IMD two-tone signals. Theoretical analysis, simulation, and experimental results all demonstrate the effectiveness of our approach.

This paper presents a non-blind watermarking technique that is robust to non-linear geometric distortion attacks. This is one of the most challenging problems for copyright protection of digital content because it is difficult to estimate the distortion parameters for the embedded blocks. In our proposed scheme, the location of the blocks are recorded by the translation parameters from multiple Scale Invariant Feature Transform (SIFT) feature points. This method is based on two assumptions: SIFT features are robust to non-linear geometric distortion and even such non-linear distortion can be regarded as “linear” distortion in local regions. We conducted experiments using 149,800 images (7 standard images and 100 images downloaded from Flickr, 10 different messages, 10 different embedding block patterns, and 14 attacks). The results show that the watermark detection performance is drastically improved, while the baseline method can achieve only chance level accuracy.

This paper proposes a low power tone recognition suitable for automatic tonal speech recognizer (ATSR). The tone recognition estimates fundamental frequency (F0) only from vowels by using a new magnitude difference function (MDF), called vowel-MDF. Accordingly, the number of operations is considerably reduced. In order to apply the tone recognition in portable electronic equipment, the tone recognition is designed using parallel and pipeline architecture. Due to the pipeline and parallel computations, the architecture achieves high throughput and consumes low power. In addition, the architecture is able to reduce the number of input frames depending on vowels, making it more adaptable depending on the maximum number of frames. The proposed architecture is evaluated with words selected from voice activation for GPS systems, phone dialing options, and words having the same phoneme but different tones. In comparison with the autocorrelation method, the experimental results show 35.7% reduction in power consumption and 27.1% improvement of tone recognition accuracy (110 words comprising 187 syllables). In comparison with ATSR without the tone recognition, the speech recognition accuracy indicates 25.0% improvement of ATSR with tone recogntion (2,250 training data and 45 testing words).

This paper describes the design of an interpolated pipeline analog-to-digital converter (ADC). By introducing the interpolation technique into the conventional pipeline topology, it becomes possible to realize a more than 10-bits resolution and several hundred MS/s ADC using low-gain open-loop amplifiers without any multiplying digital-to-analog converter (MDAC) calibration. In this paper, linearity requirement of the amplifier is analyzed with the relation of reference range and stage resolution first. Noise characteristic is also discussed with amplifier's noise bandwidth and load capacitance. After that, sampling speed and SNR characteristic are examined with various amplifier currents. Next, the resolution optimization of the pipeline stage is discussed based on the power consumption. Through the analysis, reasonable parameters for the amplifier can be defined, such as transconductance, source degeneration resistance and load capacitance. Also, optimized operating speed and stage resolution for interpolated pipelined ADC is shown. The analysis in this paper is valuable to both the design of interpolated pipeline ADCs and other circuits which incorporate interpolation and amplifiers.

A non-regular tree T with a prescribed branching sequence (s1,s2,...,sn) is a rooted and ordered tree such that its internal nodes are numbered from 1 to n in preorder and every internal node i in T has si children. Recently, Wu et al. (2010) introduced a concise representation called RD-sequences to represent all non-regular trees and proposed a loopless algorithm for generating all non-regular trees in a Gray-code order. In this paper, based on such a Gray-code order, we present efficient ranking and unranking algorithms of non-regular trees with n internal nodes. Moreover, we show that the ranking algorithm and the unranking algorithm can be run in O(n2) time and O(n2+nSn-1) time, respectively, provided a preprocessing takes O(n2Sn-1) time and space in advance, where .

This paper proposes an adaptation method for structuring elements of morphological filters. A structuring element of a morphological filter specifies a shape of local structures that is eliminated or preserved in the output. The adaptation of the structuring element is hence a crucial problem for image denoising using morphological filters. Existing adaptation methods for structuring elements require preliminary training using example images. We propose an adaptation method for structuring elements of morphological opening filters that does not require such training. In our approach, the opening filter is interpreted as an approximation method with the union of the structuring elements. In order to eliminate noise components, a penalty defined from an assumption of image smoothness is imposed on the structuring element. Image denoising is achieved through decreasing the objective function, which is the sum of an approximation error term and the penalty function. In experiments, we use the proposed method to demonstrate positive impulsive noise reduction from images.

In this paper, a novel feature named bidirectional local template patterns (B-LTP) is proposed for use in pedestrian detection in still images. B-LTP is a combination and modification of two features, histogram of templates (HOT) and center-symmetric local binary patterns (CS-LBP). For each pixel, B-LTP defines four templates, each of which contains the pixel itself and two neighboring center-symmetric pixels. For each template, it then calculates information from the relationships among these three pixels and from the two directional transitions across these pixels. Moreover, because the feature length of B-LTP is small, it consumes less memory and computational power. Experimental results on an INRIA dataset show that the speed and detection rate of our proposed B-LTP feature outperform those of other features such as histogram of orientated gradient (HOG), HOT, and covariance matrix (COV).

This paper presents the stability analysis for continuous-time Takagi-Sugeno fuzzy systems using a fuzzy Lyapunov function. The proposed fuzzy Lyapunov function involves the time derivatives of states to include new free matrices in the LMI stability conditions. These free matrices extend the solution space for Linear Matrix Inequalities (LMIs) problems. Numerical examples illustrate the effectiveness of the proposed methods.

In this paper, we describe a new method to deal with analog signal in time domain. The method converts voltage signal to time-interleaved phase modulation signal of clock edge. After being amplified by a new time amplifier (TA), phases of the signal are converted to digital codes by successive approximation time-to-digital converter (SA-TDC). The test chip includes 8 interleaved 4 bit SA-TDCs with short latency. The chip operates up to 4.4 GHz. The measured ENOB is 3.51 bit and FOM is 0.49 pJ/conv.

The heterogeneous network (HetNet), which deploys small cells such as picocells, femotcells, and relay nodes within macrocell, is regarded as a cost-efficient and energy-efficient approach to resolve increasing demand for data bandwidth and thus has received a lot of attention from research and industry. Since small cells share the same licensed spectrum with macrocells, concurrent transmission induces severe interference, which causes performance degradation, particularly when coordination among small cell base stations (BSs) is infeasible. Given the dense, massive, and unplanned deployment of small cells, mitigating interference in a distributed manner is a challenge and has been explored in recent papers. An efficient and innovative approach is to apply cognitive radio (CR) into HetNet, which enables small cells to sense and to adapt to their surrounding environments. Consequently, stations in each small cell are able to acquire additional information from surrounding environments and opportunistically operate in the spectrum hole, constrained by minimal inducing interference. This paper summarizes and highlights the CR-based interference mitigation approaches in orthogonal frequency division multiple access (OFDMA)-based HetNet networks. With special discussing the role of sensed information at small cells for the interference mitigation, this paper presents the potential cross-layer facilitation of the CR-enable HetNet.