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We present a hardware-friendly spatiotemporal compressed sensing framework for video compression. The spatiotemporal compressed sensing incorporates random sampling in both spatial and temporal domain to encode the video scene into a single coded image. During decoding, the video is reconstructed using dictionary learning and sparse recovery. The evaluation results demonstrate the proposed approach...
Energy saving in buildings has attracted many researchers attention. One of the research topics is occupancy detection for each room to automatically control airconditioner, light, heating, etc. by monitoring the temperature, humidity, light, and co2 using the corresponding sensors. For existing data analysis, traditional regression methods such as CART, RF, LDA are often used to predict the occupancy...
This paper presents a mixed-signal ASIC for triple-chamber pacemakers. The ASIC performs four major functionalities: 1) sensing of heartbeat signals; 2) measuring the heart resistance of three chambers independently to diagnose the attachment status of the electrodes and provide additional information about the pathological status of the patient's heart; 3) generating stimulus pulses with programmable...
Multi-channel neural recording devices are widely used for in vivo neuroscience experiments. Incurred by high signal frequency and large channel numbers, the acquisition rate could be on the order of hundred MB/s, which requires compression before wireless transmission. In this paper, we adopt the Compressed Sensing framework with a simple on-chip implementation. To improve the performance while reducing...
Wireless Sensor Network (WSN) is multiple hops network. Nodes near sink are required to transmit a large amount of data and expend energy rapidly. These nodes die early and outer nodes can not send data to sink. Therefore the network dies early with much unused energy. This phenomenon is called energy hole. Aiming at energy hole problem of WSN, a novel solution is proposed in this paper. According...
Robust navigation for mobile robots requires an accurate method for tracking the robot position in the environment. This paper presents a simple and novel visual-inertial integration system suitable for unstructured and unprepared indoor environments, where MARG (Magnet, Angular Rate and Gravity) sensors and a monocular camera are used. The pre-estimated orientation from MARG sensors, is used to estimate...
We demonstrate a method to build signal dependent sparse representation dictionary for neural action potentials using K-SVD algorithm and Discrete Wavelets Transform. We also show a method to utilize this dictionary to recover the neural signal in the Compressive Sensing (CS) framework. Comparing against the non-signal dependent CS recovery algorithms, this new recovery algorithm can achieve same...
In this paper, we study the cognitive interference management (CIM) scheme in the coexistence networks of macro-cells and femtocells. A single-channel detection based spectrum allocation algorithm is proposed to enhance the performance of femtocells considering the cross-tier interference and co-tier interference. The proposed scheme converts the complex interference environment into several specific...
In this paper, we consider the resource allocation problem in the uplink transmission of an orthogonal frequency-division multiple access (OFDMA) based cognitive radio (CR) network. The resource allocation aims to maximize the uplink throughput of secondary users (SUs) in CR network under the constraints of the primary user (PU) interference and the transmit power limits of SUs. In general, the optimal...
On the basis of studying conveyer belt break forecast device using X-ray systematically, the mathematical model was found and set up. And it would promote us to research the device further and optimize parameters. Firstly, the mathematical model of conveyer belt break forecast device was built for the first time by "X-ray testing model". The method avoids thoroughly the impossibilities of...
The objective of this paper is to derive a satellite attitude estimation algorithm only using vector observation from the star-sensor, in gyros-less or gyro-disable mode. State estimation is achieved through the unscented Kalman filter (UKF) based on unscented transformation. Simulation results indicate that this approach is feasible and effective
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