While there are many aspect-oriented modeling (AOM) approaches, from requirements to low-level design, it is still difficult to compare them and know under which conditions different approaches are most applicable. Th...
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In this paper, a novel approach based on non-negative matrix factorization is applied for joint spectrum sensing and primary user localization in cognitive radio networks. This approach is robust and tolerant to spars...
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In this work, we propose a recursive local linear estimator (RLLE) for identification of nonlinear autoregressive systems with exogenous inputs, along with an analysis of its strong consistency and asymptotical mean s...
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Due to tightening spectral criteria, joint optimization of radar transmitter waveform and circuit is considered to minimize the nonlinearity and waveform induced spectral spreading of radar transmitters. This work dem...
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Due to tightening spectral criteria, joint optimization of radar transmitter waveform and circuit is considered to minimize the nonlinearity and waveform induced spectral spreading of radar transmitters. This work demonstrates the ACPR load-pull measurement of a power amplifier under excitation from two chirp waveforms. The results are compared to allow selection of the optimum chirp and transmitter load impedance. This work represents a beginning effort toward the real-time, computationally intelligent transmitter optimization in future reconfigurable radar systems.
A new model is used to examine the DC output characteristics of AlGaN/GaN heterostructure field effect transistors. The model is based on the charge-control/gradualchannel approximation and takes into account the non-...
A new model is used to examine the DC output characteristics of AlGaN/GaN heterostructure field effect transistors. The model is based on the charge-control/gradualchannel approximation and takes into account the non-linear current vs. voltage characteristics of the ungated AlGaN/GaN heterostructure channel regions. The model also includes thermal effects associated with device self-heating. For the power dissipation levels considered for many applications, the thermal degradation of the carrier drift velocity is shown to cause a negative output conductance in saturation. The temperature is incorporated self-consistently into the model through the field and temperature dependent mobility obtained from Monte Carlo transport simulations for electron transport in GaN. Calculated results presented for the DC output characteristics of several AlGaN/GaN field effect transistors show a strong dependence on the thermal properties of the substrate material. The substrate materials considered in this work are sapphire, SiC, AlN, and GaN.
A hypergraph is a set V of vertices and a set of non-empty subsets of V , called hyperedges. Unlike graphs, hypergraphs can capture higher-order interactions in social and communication networks that go beyond a simpl...
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This paper presents a survey of state-of-the-art routing techniques in Wireless Sensor Networks (WSNs). Compared with traditional wireless networks, WSNs are characterized with denser levels of node deployment, higher...
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ISBN:
(纸本)9781467345217
This paper presents a survey of state-of-the-art routing techniques in Wireless Sensor Networks (WSNs). Compared with traditional wireless networks, WSNs are characterized with denser levels of node deployment, higher unreliability of sensor nodes and severe power, computation and memory constraints. Various design challenges such as energy efficiency, data delivery models, quality of service, overheads etc., for routing protocols in WSNs are highlighted. We addressed most of the proposed routing methods along with scheme designs, benefits and result analysis wherever possible. The routing protocols discussed are classified into seven categories such as Data centric routing, Hierarchical routing, Location based routing, Negotiation based routing, Multipath based routing, Quality of Service (QoS) routing and Mobility based routing. This paper also compares the routing protocols against parameters such as power consumption, scalability, mobility, optimal routing and data aggregation. The paper concludes with possible open research issues in WSNs.
Listening for engine sounds in an underwater environment is modeled using spatialized infrapitch signals and pink noise maskers. Detection thresholds for such signals were measured for various spatial configurations o...
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ISBN:
(纸本)9781627485609
Listening for engine sounds in an underwater environment is modeled using spatialized infrapitch signals and pink noise maskers. Detection thresholds for such signals were measured for various spatial configurations of maskers. All stimuli were delivered over headphones, and rendered using individually measured Head-Related Transfer Functions. In single-masker environments, no significant effect of signal bearing in azimuth or elevation on detection threshold was observed. In multi-masker environments, the largest detection threshold increase was observed when increasing the number of maskers from 1 to 2. Thereafter, a linear increase in threshold detection (in dB) for every doubling of maskers, up to 32 maskers was observed. Randomizing the spatial presentation of the signal and maskers for each trial did not affect thresholds. Results suggest that prior knowledge of the spatial configuration of the signal and maskers does not appear to be necessary in performing such detection tasks.
In many Intelligent Transportation System (ITS) applications that crowd-source data from probe vehicles, a crucial step is to accurately map the GPS trajectories to the road network in real time. This process, known a...
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ISBN:
(纸本)9781467330640
In many Intelligent Transportation System (ITS) applications that crowd-source data from probe vehicles, a crucial step is to accurately map the GPS trajectories to the road network in real time. This process, known as map-matching, often needs to account for noise and sparseness of the data because (1) highly precise GPS traces are rarely available, and (2) dense trajectories are costly for live transmission and storage. We propose an online map-matching algorithm based on the Hidden Markov Model (HMM) that is robust to noise and sparseness. We focused on two improvements over existing HMM-based algorithms: (1) the use of an optimal localizing strategy, the variable sliding window (VSW) method, that guarantees the online solution quality under uncertain future inputs, and (2) the novel combination of spatial, temporal and topological information using machine learning. We evaluated the accuracy of our algorithm using field test data collected on bus routes covering urban and rural areas. Furthermore, we also investigated the relationships between accuracy and output delays in processing live input streams. In our tests on field test data, VSW outperformed the traditional localizing method in terms of both accuracy and output delay. Our results suggest that it is viable for low-latency applications such as traffic sensing.
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