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Neuronal tuning property such as preferred direction and modulation depth could change gradually or abruptly in brain machine interface (BMI). The decoding performance will decay in static algorithms where dynamic neuronal tuning property is regarded as stationary. Many adaptive algorithms have been proposed to update the time-varying decoding parameter with main consideration on the decoding performance,...
The graph topology is the basis of graph signal processing. This paper investigates how to learn a smooth and sparse weight matrix for an undirected graph from the signals observed on the graph. The idea is based on the locally linear embedding and Bernoulli-Gaussian model, from which a nonconvex optimization problem is derived. This paper introduces a scalable algorithm to work out a sparse and smooth...
This paper studies an energy management scheme for heating, ventilation and air-conditioning (HVAC) systems of an organization over a fixed period of time. The objective is to minimize the peak demand and thus achieve a more balanced demand distribution. In this context, an optimization problem is formulated as a mixed integer linear program (MIP) subject to a set of realistic constraints. A novel...
This paper proposes a real-time algorithm that recommends battery swapping stations (BSSs) to electric taxis (ETs) that need their batteries swapped. The algorithm takes into consideration available batteries at BSSs, driving ranges of ETs and the current traffic conditions, etc, in order to avoid long queues at BSSs. We consider a basic model that assumes past decisions are perfectly executed, and...
We propose a model of a battery switching station (BSS) for electric buses (EBs) that captures the predictability of bus operation. We schedule battery charging in the BSS so that every EB arrives to find a battery ready for switching. We develop an efficient algorithm to compute an optimal schedule. It uses dual decomposition to decouple the charging decisions at different charging boxes so that...
Non-line-of-sight (NLOS) propagation, which widely exists in wireless systems, will degrade the performance of wireless positioning system if it is not taken into consideration in the localization algorithm design. The 3rd Generation Partnership Project (3GPP) suggests that the probabilities of line-of-sight (LOS) and NLOS are related to the distance between the receiver and the transmitter. In this...
This paper investigates the battery charging schedule problem of a battery-swapping station for electric buses (EB). An EB assignment policy is proposed such that there is a one-to-one correlation between EBs and batteries. By this means, the battery charging schedule problem aiming to minimize the total cost of the battery-swapping station is formulated as a constrained convex program with both spatially...
Demand response is a key solution in smart grid to address the ever-increasing peak energy consumption. With multiple utility companies, users will decide from which utility company to buy electricity and how much to buy. Consequently, how to devise distributed real-time demand response in the multiseller̈Cmultibuyer environment emerges as a critical problem in future smart grid. In this paper, we...
This paper investigates the optimal charging strategy for a plug-in electric taxi (PET) to maximize its operating profit by choosing proper charging slots, subject to uncertain electricity prices and time-varying incomes. As PET consumes more electricity and possesses different charging behaviors from the widely studied private electric vehicles, this problem deserves special treatment. First, in...
This paper studies the optimal charging problem for future plug-in electric taxi (PET) with time-varying profits, i.e., time-varying service incomes and charging costs. Aiming at maximizing the average profit of a PET in long term under the constraint of state of charge (SoC) dynamics of PET battery, this problem is formulated as a constrained binary programming problem in infinite time horizon. The...
Recent years have witnessed the significant growth in electricity consumption. The emerging smart grid aims to address the ever-increasing load through appropriate scheduling, i.e., to shift the energy demand from peak to off-peak periods by pricing tariffs as incentives. Under the real-time pricing environment, due to the uncertainty of future prices, load scheduling is formulated as an optimization...
This paper investigates joint scheduling problem of large-scale smart appliances and batteries (e.g., in a smart building), to minimize electricity payment, user's dissatisfaction and battery loss under kinds of constraints. Due to the binary nature of charge and discharge states of battery, this problem is formulated as a constrained mixed-integer nonlinear program. In order to solve it efficiently,...
The size of target will induce a degradation of tracking performance, which has been neglected for simplicity in most previous studies. In multiple target tracking, occlusions will be caused by target size effect, one target can become a moving obstacle blocking the direct channel between the anchor and another target. In this paper, the data association problem in multiple target tracking is investigated...
We develop a mathematical programming approach to schedule meetings in an organization over a fixed period of time, while minimizing the wasted energy and possibly achieving more balanced demand distribution. The problem is formulated as a mixed integer linear program subject to a set of realistic constraints including people's available time slots and energy consumption characteristics of the meeting...
This paper investigates the scheduling problem of an intermediary charging station with multiple electric vehicles (EV) in real-time electricity pricing environment. A charging aggregator (CA) is in charge to coordinate EVs' charging so that all EVs' requirements are met and meanwhile the total social cost is minimized. Besides, a new charging mechanism named Vehicle-to-Vehicle (V2V) is proposed to...
This paper aims at scheduling the charging behavior of a large population of plug-in electric taxis (PET) by means of pricing, in order to respond to load requirement of future smart grid in critical situations. The main contributions consist of two parts. First, the charging behavior of a single PET is analyzed, and a threshold-based scheduling algorithm is proposed from the perspective of PET in...
Smart grid has been widely considered to be the next generation of power grid, which incorporates smart meters and two-way communications to improve the agility, reliability, efficiency, security, economy and environmental friendliness. One of the key foundations of smart grid is real-time access to meter data via a reliable communication infrastructure. In this paper, we introduce promising wireless...
Knowing channel sight condition is important as it has a great impact on localization performance. In this paper, a RSS-based localization algorithm, which jointly takes into consideration the effect of channel sight conditions, is investigated. In our approach, the channel sight conditions experience by a moving target to all sensors is modeled as a hidden Markov model (HMM), with the quantized measured...
This paper concentrates on the optimal scheduling of electric vehicle (EV). The EV is scheduled for both operating stage and non-operating stage. With full consideration of operating income, regulation revenue and the owner's habit, the cost minimization problem is formulated as a convex programming with coupling constrains. Dual decomposition is utilized to obtain the global optimal solution. Then,...
Demand response management (DRM) is one of the main features in smart grid, which is realized via communications between power providers and consumers. Due to the vulnerabilities of communication channels, communication is not perfect in practice and will be threatened by jamming attack. In this paper, we consider jamming attack in the wireless communication for smart grid. Firstly, the DRM performance...
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