• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.27 no.7B
• /
• pp.664-672
• /
• 2002

This paper analyzes a sequential estimator with flexible structure for rapid acquisition of the m-sequence signals. If the received PN chips stored in the estimator's internal registers as initial loading values include one error, this chip with error can be corrected through multiple local PN code generators to achieve high-speed acquisition performance. Hamming distance between regenerated local PN codes from the proposed system and received PN code is compared with given threshold to choose a possible correct path and to declare success of the code acquisition. Using signal flow graph, average acquisition time that depends on detection and false alarm probability is calculated. By modifying generally used matched filter structure for PN code acquisition, the proposed system provides flexible structure and rapid acquisition process.

• Journal of the Korean Institute of Telematics and Electronics S
• /
• v.35S no.7
• /
• pp.72-85
• /
• 1998

In this paper, we propose a new method that sequentially estimates TDOA(Time Delay Of Arrival) and FDOA(Frequency Delay Of Arrival) for extracting the information about the bearing and relative velocity of a target in passive radar or sonar arrays. The objective is to efficiently estimate the TDOA and FDOA between two sensor signal measurements, corrupted by correlated Gaussian noise sources in an unknown way. The proposed method utilizes the one dimensional slice function of the third order cumulants between the two sensor measurements, by which the effect of correlated Gaussian measurement noises can be significantly suppressed for the estimation of TDOA. Because the proposed sequential algoritjhm uses the one dimensional complex ambiguity function based on the TDOA estimate from the first step, the amount of computations needed for accurate estimationof FDOA can be dramatically reduced, especially for the cases where high frequency resolution is required. It is demonstrated that the proposed algorithm outperforms existing TDOA/FDOA estimation algorithms based on the ML(maximum likelihood) criterionandthe complex ambiguity function of the third order cumulant as well, in the MSE(mean squared error) sense and computational burden. Various numerical resutls on the detection probability, MSE and the floatingpoint computational burden are presented via Monte-Carlo simulations for different types of noises, different lengths of data, and different signal-to-noise ratios.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.56 no.8
• /
• pp.1424-1429
• /
• 2007

This paper presents a simple and reliable one-touch type multi-immunosensing lab-on-a-chip (LOC) detecting antibodies as multi-disease markers using electrochemical method suitable for a portable point-of-care system (POCS). The multi-stacked LOC consists of a PDMS space layer for liquids loading, a PDMS valve layer with 50 im in height for the membrane, a PDMS channel layer for the fluid paths, and a glass layer for multi electrodes. For the disposable immunoassay which needs sequential flow control of sample and buffer liquids according to the designed strategies, reliable and easy-controlled on-chip operation mechanisms without any electric power are necessary. The driving forces of sequential liquids transfer are the capillary attraction force and the pneumatic pressure generated by air bladder push. These passive fluid transport mechanisms are suitable for single-use LOC module. Prior to the application of detection of the antibody as a disease marker, the model experiments were performed with anti-DNP antibody and anti-biotin antibody as target analytes. The flow test results demonstrate that we can control the fluid flow easily by using the capillary stop valve and the PDMS check valves. By the model tests, we confirmed that the proposed LOC is easily applicable to the bioanalytic immunosensors using bioelectrocatalysis.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.21 no.3
• /
• pp.329-334
• /
• 2011

This paper presents the method for location estimation with obstacle tracking method. A laser scanner is used to implement the system, and we assume that the map information is known. We matches the measurement of the laser scanner to estimate the location of the robot by using sequential monte carlo (SMC) method. After estimating the robot's location, the pose of obstacles are detected and tracked, hence, we can predict the collision risk of them. Finally, we present the experiment results to verify the proposed method.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.9 no.5
• /
• pp.205-211
• /
• 2009

The Weightless Neural Network(WNN) has the advantage of the processing speed, less computability than weighted neural network which readjusts the weight. Especially, The behavior information such as sequential gesture has many serial correlation. So, It is required the high computability and processing time to recognize. To solve these problem, Many algorithms used that added preprocessing and hardware interface device to reduce the computability and speed. In this paper, we proposed the Ram based Sequential Cumulative Neural Network(SCNN) model which is sign language recognition system without preprocessing and hardware interface. We experimented with using compound words in continuous korean sign language which was input binary image with edge detection from camera. The recognition system of sign language without preprocessing got 93% recognition rate.

• Asian Pacific Journal of Cancer Prevention
• /
• v.14 no.6
• /
• pp.3843-3846
• /
• 2013

Objective: The purpose of this study was to assess prognosis after resection of giant tumors (including lobectomy or pneumonectomy) in the mediastinum. Materials and Methods: Patients with resection of a giant tumor in the mediastinum of the thoracic cavity received ICU treatment including dynamic monitoring of vital signs, arterial blood pressure and CVP detection, determination of hemorrhage, pulmonary function and blood gas assay, treatment of relevant complications, examination and treatment with fiber optic bronchoscopy, transfusion and hemostasis as well as postoperative removal of ventilators by invasive and non-invasive sequential mechanical ventilation technologies. Results: Six patients were rehabilitated successfully after ICU treatment with controlled postoperative errhysis and pulmonary infection by examination and treatment with fiber optic bronchoscopy without second application of ventilators and tubes after sequential mechanical ventilation technology. One patient died from multiple organ failure under ICU treatment due to postoperative active hemorrhage after second operative hemostasis. Conclusions: During peri-operative period of resection of giant tumor (including lobectomy or pneumonectomy) in mediastinum ofthe thoracic cavity, the ICU plays an important role in dynamic monitoring of vital signs, treatment of postoperative stress state, postoperative hemostasis and successful removal of ventilators after sequential mechanical ventilation.

• Journal of Digital Convergence
• /
• v.13 no.10
• /
• pp.287-293
• /
• 2015

This study proposed signal processing techniques and neural network with weighted fuzzy membership functions(NEWFM) to detect epileptic seizure from EEG signals. This study used wavelet transform(WT), sequential increment method, and phase space reconstruction(PSR) as signal processing techniques. In the first step of signal processing techniques, wavelet coefficients were extracted from EEG signals using the WT. In the second step, sequential increment method was used to extract peaks from the wavelet coefficients. In the third step, 3D diagram was produced from the extracted peaks using the PSR. The Euclidean distances and statistical methods were used to extract 16 features used as inputs for NEWFM. The proposed methodology shows that accuracy, specificity, and sensitivity are 97.5%, 100%, 95% with 16 features, respectively.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.37 no.7A
• /
• pp.535-544
• /
• 2012

Multi-Input Multi-Output (MIMO) transmission is now considered as one of essential techniques enabling high rate data transmissions in wireless communication systems. In addition, severe channel impairments in wireless systems should be compensated by using highly efficient forward error correction (FEC) codes. Turbo codes or low density parity check (LDPC) codes, using iterative decoding with soft decision detection information (SDDI), are the most common examples. The excellent performance of these codes should be conditioned on accurate estimation of SDDI from the MIMO detection process. In this paper, we propose a soft MIMO detection scheme using QR decomposition of channel matrices as an efficient means to provide accurate SDDI to the iterative decoder. The proposed method employed a two sequential soft MIMO detection process in order to reduce computational complexity. Compared to the soft ZF method calculating the direct inverse of the channel matrix, the complexity of the proposed method can be further reduced as the number of antennas is increased, without any performance degradation.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.14 no.12
• /
• pp.2783-2790
• /
• 2010

In this paper, we first review LDPC codes in general and a belief propagation algorithm that works in logarithm domain. LDPC codes, which is chosen 802.11n for wireless local access network(WLAN) standard, require a large number of computation due to large size of coded block and iteration. Therefore, we presented three kinds of low computational algorithms for LDPC codes. First, sequential decoding with partial group is proposed. It has the same H/W complexity, and fewer number of iterations are required with the same performance in comparison with conventional decoder algorithm. Secondly, we have apply early stop algorithm. This method reduces number of unnecessary iterations. Third, early detection method for reducing the computational complexity is proposed. Using a confidence criterion, some bit nodes and check node edges are detected early on during decoding. Through the simulation, we knew that the iteration number are reduced by half using subset algorithm and early stop algorithm is reduced more than one iteration and computational complexity of early detected method is about 30% offs in case of check node update, 94% offs in case of check node update compared to conventional scheme. The LDPC decoder have been implemented in Xilinx System Generator and targeted to a Xilinx Virtx5-xc5vlx155t FPGA. When three algorithms are used, amount of device is about 45% off and the decoding speed is about two times faster than convectional scheme.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.30 no.4C
• /
• pp.283-289
• /
• 2005

In this paper, we propose two efficient symbol detection algorithms for space-frequency OFDM (SF-OFDM) transmit diversity scheme. When the number of sub-carriers in SF-OFBM scheme is small, the interference between adjacent sub-carriers may be generated. The proposed algorithms eliminate this interference in a parallel or sequential manlier and achieve a considerable performance improvement over the conventional detection algorithm. The bit error rate (BER) performance of the proposed detection algorithms is evaluated by the simulation. In the case of 2 transmit and 2 receive antennas, at $BER=10^{-4}$ the proposed algorithms achieve the gain improvement of about 3 dB. The symbol detectors with the proposed algorithms are designed in a hardware description language and synthesized to gate-level circuits with the $0.18{\mu}m$ 1.8V CMOS standard cell library. With the division-free architecture, the proposed SF-OFDM-PIC and SF-OFDM-SIC symbol detectors can be implemented using 140k and 129k logic gates, respectively.