While different parties have been rivaling for a national handset television standard, the China Association for Standardization (CAS) recently became a powerful rival in the national competition by issuing its of... While different parties have been rivaling for a national handset television standard, the China Association for Standardization (CAS) recently became a powerful rival in the national competition by issuing its official handset television standard (CDMB), for which it owns intellectual property rights. Last October, the broadcast and TV system had issued its own professional standard. Now, there is some concern about the launch of a national handset television standard, since the CAS has such a special status.……展开更多
A high-performance, low cost inverse integer transform architecture for advanced video standard （AVS） video coding standard was presented. An 8 × 8 inverse integer transform is required in AVS video system whic...A high-performance, low cost inverse integer transform architecture for advanced video standard （AVS） video coding standard was presented. An 8 × 8 inverse integer transform is required in AVS video system which is compute-intensive. A hardware transform is inevitable to compute the transform for the real-time application. Compared with the 4 × 4 transform for H.264/AVC, the 8 × 8 integer transform is much more complex and the coefficient in the inverse transform matrix Ts is not inerratic as that in H.264/AVC. Dividing the Ts into matrix Ss and Rs, the proposed architecture is implemented with the adders and the specific CSA-trees instead of multipliers, which are area and time consuming. The architecture obtains the data processing rate up to 8 pixels per-cycle at a low cost of area. Synthesized to TSMC 0.18 μm COMS process, the architecture attains the operating frequency of 300 MHz at cost of 34 252 gates with a 2-stage pipeline scheme. A reusable scheme is also introduced for the area optimization, which results in the operating frequency of 143 MHz at cost of only 19 758 gates.展开更多
Broadcasting gateway equipment generally uses a method of simply switching to a spare input stream when a failure occurs in a main input stream.However,when the transmission environment is unstable,problems such as re...Broadcasting gateway equipment generally uses a method of simply switching to a spare input stream when a failure occurs in a main input stream.However,when the transmission environment is unstable,problems such as reduction in the lifespan of equipment due to frequent switching and interruption,delay,and stoppage of services may occur.Therefore,applying a machine learning(ML)method,which is possible to automatically judge and classify network-related service anomaly,and switch multi-input signals without dropping or changing signals by predicting or quickly determining the time of error occurrence for smooth stream switching when there are problems such as transmission errors,is required.In this paper,we propose an intelligent packet switching method based on the ML method of classification,which is one of the supervised learning methods,that presents the risk level of abnormal multi-stream occurring in broadcasting gateway equipment based on data.Furthermore,we subdivide the risk levels obtained from classification techniques into probabilities and then derive vectorized representative values for each attribute value of the collected input data and continuously update them.The obtained reference vector value is used for switching judgment through the cosine similarity value between input data obtained when a dangerous situation occurs.In the broadcasting gateway equipment to which the proposed method is applied,it is possible to perform more stable and smarter switching than before by solving problems of reliability and broadcasting accidents of the equipment and can maintain stable video streaming as well.展开更多
文摘 While different parties have been rivaling for a national handset television standard, the China Association for Standardization (CAS) recently became a powerful rival in the national competition by issuing its official handset television standard (CDMB), for which it owns intellectual property rights. Last October, the broadcast and TV system had issued its own professional standard. Now, there is some concern about the launch of a national handset television standard, since the CAS has such a special status.……
文摘A high-performance, low cost inverse integer transform architecture for advanced video standard （AVS） video coding standard was presented. An 8 × 8 inverse integer transform is required in AVS video system which is compute-intensive. A hardware transform is inevitable to compute the transform for the real-time application. Compared with the 4 × 4 transform for H.264/AVC, the 8 × 8 integer transform is much more complex and the coefficient in the inverse transform matrix Ts is not inerratic as that in H.264/AVC. Dividing the Ts into matrix Ss and Rs, the proposed architecture is implemented with the adders and the specific CSA-trees instead of multipliers, which are area and time consuming. The architecture obtains the data processing rate up to 8 pixels per-cycle at a low cost of area. Synthesized to TSMC 0.18 μm COMS process, the architecture attains the operating frequency of 300 MHz at cost of 34 252 gates with a 2-stage pipeline scheme. A reusable scheme is also introduced for the area optimization, which results in the operating frequency of 143 MHz at cost of only 19 758 gates.
基金This work was supported by a research grant from Seoul Women’s University(2023-0183).
文摘Broadcasting gateway equipment generally uses a method of simply switching to a spare input stream when a failure occurs in a main input stream.However,when the transmission environment is unstable,problems such as reduction in the lifespan of equipment due to frequent switching and interruption,delay,and stoppage of services may occur.Therefore,applying a machine learning(ML)method,which is possible to automatically judge and classify network-related service anomaly,and switch multi-input signals without dropping or changing signals by predicting or quickly determining the time of error occurrence for smooth stream switching when there are problems such as transmission errors,is required.In this paper,we propose an intelligent packet switching method based on the ML method of classification,which is one of the supervised learning methods,that presents the risk level of abnormal multi-stream occurring in broadcasting gateway equipment based on data.Furthermore,we subdivide the risk levels obtained from classification techniques into probabilities and then derive vectorized representative values for each attribute value of the collected input data and continuously update them.The obtained reference vector value is used for switching judgment through the cosine similarity value between input data obtained when a dangerous situation occurs.In the broadcasting gateway equipment to which the proposed method is applied,it is possible to perform more stable and smarter switching than before by solving problems of reliability and broadcasting accidents of the equipment and can maintain stable video streaming as well.
