内蒙古有线电视台全区联网信号的几种接法

１９９４年１０月内蒙古有线电视台把自办第一套电视节目通过全区５０００多公里的微波线路传向全区，即传送了全区有线电视联网信号。本文结合我区的情况介绍了内蒙有线电视台全区联网信号的几种接法供参考。

Measurement of a thin layer's thickness using independent component analysis of ground penetrating radar data

To detect overlapped echoes due to the thin pavement layers,we present a thickness measurement approach for the very thin layer of pavement structures.The term "thin" is relative to the incident wavelength or pulse.By means of independent component analysis of noisy signals received by a single radar sensor,the overlapped echoes can be successfully separated.Once the echoes from the top and bottom side of a thin layer have been separated,the time delay and the layer thickness determination follow immediately.Results of the simulation and real data verify the feasibility of the presented method.

Electric Wheelchair Control System Using Brain-Computer Interface Based on Alpha-Wave Blocking

A brain-computer interface(BCI)-based electric wheelchair control system was developed, which enables the users to move the wheelchair forward or backward, and turn left or right without any pre-learning. This control system makes use of the amplitude enhancement of alpha-wave blocking in electroencephalogram(EEG) when eyes close for more than 1 s to constitute a BCI for the switch control of wheelchair movements. The system was formed by BCI control panel, data acquisition, signal processing unit and interface control circuit. Eight volunteers participated in the wheelchair control experiments according to the preset routes. The experimental results show that the mean success control rate of all the subjects was 81.3%, with the highest reaching 93.7%. When one subject's triggering time was 2.8 s, i.e., the flashing time of each cycle light was 2.8 s, the average information transfer rate was 8.10 bit/min, with the highest reaching 12.54 bit/min.

Classification of Ultrasonic Signs Pre-processed by Fourier Transform through Artificial Neural Network Using the Echo Pulse Technique for the Identification of Defects in Welded Joints of Structural Steel

It is due to the need to ensure the security and integrity of equipment, that the non-destructive tests have been increasingly used in the industrial sector. Among these, the ultrasonic pulse echo technique is the most used in industry, mainly for its simplicity and efficiency. With one transducer only, it is possible to emit the ultrasonic and receive the echo pulse. The ANNs （artificial neural networks） are artificial intelligence techniques that, when properly trained, align themselves to inspection tests becoming a powerful tool in the detection and fault identification. In this work, the echo pulse technique was used to detect discontinuities in welds, where ANNs were fed from the information obtained by digital signal processing techniques （Fourier transform）, to identify and classify three distinct classes of defects. Results showed that with the combination of feature extraction by Fourier transformation and classification with neural networks, it is possible to obtain an automatic defect detection system in welded joints with average efficiency.

High Sensitivity Acquisition Algorithm for DSSS Signal with Data Modulation

In direct sequence spread spectrum communication both for satelliteto-ground and inter-satellite links, the system constrains due to radio frequency spectral occupation, channel data throughput and link performances in terms of data channel coding which might result in a signal structure where the symbol duration is shorter than the pseudo code period. This can generate some difficulties in the DSSS signal acquisition due to the polarity inversion caused by the data modulation. To eliminate the influence due to polarity inversion, this paper proposes a novel acquisition algorithm based on the simultaneous search of the code phase, data phase and Doppler frequency. In the proposed algorithm the data phase is predicted and the correlation period for the coherent integration can be set equal to the symbol duration. Then non-coherent accumulation over different symbol is implemented in order to enhance the acquisition algorithm sensitivity; the interval of non-coherent accumulation is the least common multiple between the symbol duration and the pseudo code period. The algorithm proposed can largely minimize the SNR loss caused by data polarity inversion and enhance acquisition performance without a noticeable increase in hardware complexity. Theoretical analysis, simulation and measured results verify the validity of the algorithm.

Study of Signal Processing Algorithm in the Receiving End of Through-the-Earth Communications of Elastic Wave

In the research of elastic wave signal detection algorithm, a method based on adaptive wavelet analysis and segmentation threshold processing of the channel noise removal methods is suggested to overcome the effect of noise, which is prcduced by absorption loss, scattering loss, reflection loss and multi-path effect during the elastic wave in the transmission undelgroound. The method helps to realize extraction and recovery of weak signal of elastic wave from the multi-path channel, and simulation study is carded out about wavelet de-noising effects of the elastic wave and obtained satisfactory results.

Olfactory Decoding Method Using Neural Spike Signals

This paper presents a novel method for inferring the odor based on neural activities observed from rats' main olfactory bulbs.Multi-channel extra-cellular single unit recordings are done by micro-wire electrodes(Tungsten,50 μm,32 channels)implanted in the mitral/tufted cell layers of the main olfactory bulb of the anesthetized rats to obtain neural responses to various odors.Neural responses as a key feature are measured by subtraction firing rates before stimulus from after.For odor inference,a decoding method is developed based on the ML estimation.The results show that the average decoding accuracy is about 100.0%,96.0%,and 80.0% with three rats,respectively.This work has profound implications for a novel brain-machine interface system for odor inference.

Recent progress in Bistatic SAR with illuminators of opportunity

Bistatic SAR（Bi SAR）with illuminators of opportunity is a kind of flexible SAR system that consists of non-cooperative transmitters and a stationary or moving receiver,as Figure 1shows.In recent years,notable efforts have been made to promote the development of this kind of system.Progress regarding Bi SAR with navigation satellites as transmitters before 2015,including the related theory and practice,has been well reviewed by Antoniou et al.and can be referred from[1].This paper reviews some of the progress in 2015and 2016,including novel signal processing approaches,advanced Bi SAR system configurations and potentially