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The use of video streaming is constantly increasing. High-resolution video requires resources on both the sender and the receiver side. Many compression techniques can be utilized to compress the video and simultaneously maintain quality. The main goal of this paper is to provide an overview of video streaming and QoE. This paper describes the basic concepts and discusses existing methodologies to measure QoE. Subjective, objective, and video compression technologies are discussed. This review paper gathers the codec implementation developed by MPEG, Google, and Apple. This paper outlines the challenges and future research directions that should be considered in the measurement and assessment of the quality of experience for video services.

Copyright of Journal of Harbin Institute of Technology. Social Sciences Edition / Haerbin Gongye Daxue Xuebao. Shehui Kexue Ban is the property of Harbin Institute of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The use of video streaming is constantly increasing. High-resolution video requires resources on both the sender and the receiver side. Many compression techniques can be utilized to compress the video and simultaneously maintain quality. The main goal of this paper is to provide an overview of video streaming and QoE. This paper describes the basic concepts and discusses existing methodologies to measure QoE. Subjective, objective, and video compression technologies are discussed. This review paper gathers the codec implementation developed by MPEG, Google, and Apple. This paper outlines the challenges and future research directions that should be considered in the measurement and assessment of the quality of experience for video services. [ABSTRACT FROM AUTHOR]

This paper proposes a deep learning approach for accurate pose estimation in ship unloaders, improving grasping accuracy by reconstructing 3D coordinates. A convolutional neural network optimizes depth map prediction from RGB images, further enhanced by a conditional generative adversarial network to refine quality. Evaluation of simulated ship unloading tasks showed over 90% grasping success rate, outperforming baseline methods. This research offers valuable insights into advanced visual perception and deep learning for next-generation automated cargo handling. [ABSTRACT FROM AUTHOR]

Abstract Purpose Convolution operator-based neural networks have shown great success in medical image segmentation over the past decade. The U-shaped network with a codec structure is one of the most widely used models. Transformer, a technology used in natural language processing, can capture long-distance dependencies and has been applied in Vision Transformer to achieve state-of-the-art performance on image classification tasks. Recently, researchers have extended transformer to medical image segmentation tasks, resulting in good models. Methods This review comprises publications selected through a Web of Science search. We focused on papers published since 2018 that applied the transformer architecture to medical image segmentation. We conducted a systematic analysis of these studies and summarized the results. Results To better comprehend the benefits of convolutional neural networks and transformers, the construction of the codec and transformer modules is first explained. Second, the medical image segmentation model based on transformer is summarized. The typically used assessment markers for medical image segmentation tasks are then listed. Finally, a large number of medical segmentation datasets are described. Conclusion Even if there is a pure transformer model without any convolution operator, the sample size of medical picture segmentation still restricts the growth of the transformer, even though it can be relieved by a pretraining model. More often than not, researchers are still designing models using transformer and convolution operators.

Purpose: Convolution operator-based neural networks have shown great success in medical image segmentation over the past decade. The U-shaped network with a codec structure is one of the most widely used models. Transformer, a technology used in natural language processing, can capture long-distance dependencies and has been applied in Vision Transformer to achieve state-of-the-art performance on image classification tasks. Recently, researchers have extended transformer to medical image segmentation tasks, resulting in good models. Methods: This review comprises publications selected through a Web of Science search. We focused on papers published since 2018 that applied the transformer architecture to medical image segmentation. We conducted a systematic analysis of these studies and summarized the results. Results: To better comprehend the benefits of convolutional neural networks and transformers, the construction of the codec and transformer modules is first explained. Second, the medical image segmentation model based on transformer is summarized. The typically used assessment markers for medical image segmentation tasks are then listed. Finally, a large number of medical segmentation datasets are described. Conclusion: Even if there is a pure transformer model without any convolution operator, the sample size of medical picture segmentation still restricts the growth of the transformer, even though it can be relieved by a pretraining model. More often than not, researchers are still designing models using transformer and convolution operators. [ABSTRACT FROM AUTHOR]

This paper investigates the optimal tracking performance based on the codec, colored noise, and bandwidth constraints in the network time‐delay systems. Choosing the optimal two‐degree‐of‐freedom compensator and the dominant expression of the system optimal tracking performance is obtained after Youla parameterization by using the coprime factorizations method and spectral decomposition technology. The result shows that the tracking performance of the system is determined by the nonminimum phase zero and unstable pole of the controlled plant. Moreover, codec, colored noise, and bandwidth constraints can also significantly impact the performance. Finally, two simulation examples prove the accuracy of the theory. [ABSTRACT FROM AUTHOR]

Currently, the multiprotocol label switching (MPLS) standard is extremely prevalent. By exploiting the features provided by MPLS technology, a range of services, including IP telephony, have enhanced their overall performance. However, due to the size of the packet header, the IP telephony service consumes a significant portion of the MPLS network's available bandwidth. For instance, in IP telephony over MPLS networks, the packet header might account for as much as 80% of lost time and bandwidth. Designers working on IP telephony are making substantial efforts to address this issue. This study contributes to current efforts by proposing a novel approach called Tel-MPLS, which involves IP telephony over MPLS. TelMPLS approach uses the superfluous fields in the IP telephony packet's header to retain the packet data, therefore lowering or zeroing the IP telephony packet's payload. Tel-MPLS is an approach that significantly reduces the bandwidth of IP telephony MPLS networks. According to the findings, the Tel-MPLS approach is capable of reducing the amount of bandwidth that is lost by 12% when using the G.729 codec. [ABSTRACT FROM AUTHOR]

We present in this article a detection system of ultrasounographic signal (USG) dedicated to the measurement of parietal rheology in human carotid artery. The aim of this practical work is to develop an ultrasonic method capable of visualizing the localized velocity profile of the carotid artery wall. The device produced makes it possible to take the USG signal from carotid wall of the human neck. It comprises an ultrasonic contact probe applied during the measurement (sensor), a signal shaping circuit, an acquisition and digitization interface in conjunction with an RS232 serial communication port and a local computer terminal hosting a graphical user interface (GUI) implemented in Visual Basic integrated development environment enabling the display, archiving and the digital processing of parietal ultrasonic signal. The aim of this study is to reconnoitering the possibility of using ultrasound for a continuous and non-invasive measurement of the arteries parietal rheology. In this work, a sensor of ultrasound is used to measure the movement and the speed of the carotid artery wall, an image of the arteries parietal rheology. [ABSTRACT FROM AUTHOR]

Vehicle Detection algorithms run on deep neural networks. But one problem arises, when the vehicle scale keeps on changing then we may get false detection or even sometimes no detection at all, especially when the object size is tiny. Then algorithms like CNN, fast-RCNN, and faster-RCNN have a high probability of missed detection. To tackle this situation YOLOv3 algorithm is being used. In the codec module, a multi-level feature pyramid is added to resolve multi-scale vehicle detection problems. The experiment was carried out with the KITTI dataset and it showed high accuracy in several environments including tiny vehicle objects. YOLOv3 was able to meet the application demand, especially in traffic surveillance Systems. [ABSTRACT FROM AUTHOR]

The existing architectures used in the multiparty audio conferencing systems are typically categorized as either centralized or decentralized. These architectures expose a trade-off between processing latency and system capacity, namely the number of participants. This paper proposes a multiparty audio conferencing system for mobile users to improve the processing latency and system capacity. Instead of using the pure centralized or decentralized architecture, the proposed system adopts a novel cooperation-based architecture, in which only some participants are selected as the central controllers to deal with the tasks such as acoustic echo cancellation, encoding, decoding, mixing and de-mixing. The proposed system also uses a buffer reordering scheme to solve the problems of network jitters and out-of-order packets. This study analyzed the processing latency of the multiparty audio conferencing systems using the existing and proposed architectures. We also implemented these systems on diverse mobile platforms to compare the processing latency and number of participants. Performance evaluation results confirmed that the proposed cooperation-based architecture can not only reduce the processing latency but also support more participants, compared to the existing architectures. [ABSTRACT FROM AUTHOR]

An efficient Reed-Solomon redundant arrays of independent disks 6 (RS-RAID 6) exclusive OR (XOR) accelerator with a scaling scheme is proposed in this paper. The accelerator first considers the hardware working characteristic to reduce the complexity of codec computation. To increase efficiency, the parameter calculation of the 8-bit Galois field [GF(8)] is converted to a GF(2) calculation, where two additions, one multiplication, and one division are optimized in every 8 bits of calculation. A new scaling scheme is also proposed to guarantee the input/output (I/O) balance. The proposed Reed-Solomon (RS) codec hardware architecture is fully verified at the Real Time Logistics (RTL) level and synthesized with a GF 12 nm technology library to compare the gate cost and input/output operations per second (IOPS) performance with those of other classic solutions. Separate simulations are performed for different codec algorithms and scaling schemes. The IOPS performance of the proposed RS-RAID 6 XOR accelerator is improved by a factor of 2-3 at the cost of 47% more gates. [ABSTRACT FROM AUTHOR]

Nowadays, as the vivid visual enjoyment requiring in mobile display devices exploding everywhere, enormous bandwidth pressure lands in all high-speed digital transmission interfaces, such as HDMI, MIPI, DP, eDP etc. A low latency in pixels' time, flexible implementation for circuits, and high performance in visual quality video stream encoder and decoder (FHP-Codec) is proposed to relax the stress. The image structural features are analyzed, which directs an accurate 1D or 2D prediction reducing the redundancy utmost compared with DSC by 10~20% benefit in entropy, without obvious increments in circuit area and power consumption. According to the benchmark in Kodak image suite, FHP-Codec shows a considerable cost-performance ratio for display driver application fields. [ABSTRACT FROM AUTHOR]

The demand for the telecommunication services, such as IP telephony, has increased dramatically during the COVID-19 pandemic lockdown. IP telephony should be enhanced to provide the expected quality. One of the issues that should be investigated in IP telephony is bandwidth utilization. IP telephony produces very small speech samples attached to a large packet header. The header of the IP telephony consumes a considerable share of the bandwidth allotted to the IP telephony. This wastes the network's bandwidth and influences the IP telephony quality. This paper proposes a mechanism (called Smallerize) that reduces the bandwidth consumed by both the speech sample and the header. This is achieved by assembling numerous IP telephony packets in one header and use the header's fields to carry the speech sample. Several metrics have been used to measure the achievement Smallerize mechanism. The number of calls has been increased by 245.1% compared to the typical mechanism. The bandwidth saving has also reached 68% with the G.28 codec. Therefore, Smallerize is a possible mechanism to enhance bandwidth utilization of the IP telephony. [ABSTRACT FROM AUTHOR]

IP Phone merupakan salah perangkat pada Voice over Internet Protocol (VoIP) yang dapat menyalurkan suara menggunakan IP. Berbagai tipe IP Phone bermunculan dengan harga dan fitur yang bervariasi, sehingga menimbulkan pertanyaan terkait bagaimana perbandingan kualitas suara pada IP Phone yang dihadirkan oleh berbagai tipe tersebut, mengingat kualitas suara dalam telekomunikasi sangat penting agar tidak menimbulkan kesalahfahaman saat telekomunikasi berlangsung. Terdapat dua tipe IP Phone pada sistem yang sudah diregistrasikan dengan server sehingga dapat melakukan panggilan dengan range frekuensi 300Hz s/d 3400Hz, kemudian dari komunikasi antar IP Phone terdapat bentuk gelombang sinyal informasi input dan output, respon amplitudo suara terhadap perubahan frekuensi suara serta nilai delay dari pergeseran fasa menggunakan alat ukur Tranmission Test Set dan Oscilloscope yang digunakan untuk mengetahui karakter kualitas suara dalam komunikasi antar IP Phone sesuai hasil uji parameter. Hasil pengujian sitem dapat disimpulkan bahwa bentuk gelombang sinyal informasi input dan output pada frekuensi suara memiliki bentuk gelombang sinus, namun gelombang output pada IP Phone tipe A frekuensi 300Hz s/d 1100Hz dan IP Phone tipe B frekuensi 300Hz s/d 1300Hz mengalami distorsi, selanjutnya dari hasil nilai Peak to Peak gelombang diketahui adanya penguatan tegangan yaitu semakin besar nilai frekuensi pada input maka akan semakin kecil nilai penguatan tegangan yang dihasilkan. Nilai respon amplitudo terhadap perubahan frekuensi suara dengan nilai amplitudo input -23.5 dBm pada kedua IP Phone memiliki penguatan daya yang semakin kecil ketika nilai frekuensi suara semakin tinggi. Nilai delay yang didapatkan dari pergeseran gelombang input dan output antar IP Phone yaitu kurang dari 150 ms.

Effective prediction of wastewater treatment is beneficial for precise control of wastewater treatment processes. The nonlinearity of pollutant indicators such as chemical oxygen demand (COD) and total phosphorus (TP) makes the model difficult to fit and has low prediction accuracy. The classical deep learning methods have been shown to perform nonlinear modeling. However, there are enormous numerical differences between multi-dimensional data in the prediction problem of wastewater treatment, such as COD above 3000 mg/L and TP around 30 mg/L. It will make current normalization methods challenging to handle effectively, leading to the training failing to converge and the gradient disappearing or exploding. This paper proposes a multi-factor prediction model based on deep learning. The model consists of a combined normalization layer and a codec. The combined normalization layer combines the advantages of three normalization calculation methods: z-score, Interval, and Max, which can realize the adaptive processing of multi-factor data, fully retain the characteristics of the data, and finally cooperate with the codec to learn the data characteristics and output the prediction results. Experiments show that the proposed model can overcome data differences and complex nonlinearity in predicting industrial wastewater pollutant indicators and achieve better prediction accuracy than classical models. [ABSTRACT FROM AUTHOR]

• A novel fuzzy adaptive network predicts greenhouse climate over long periods. • Fuzzy preprocessing and adaptive normalization mitigate data volatility impact. • The model shows superior long-term predictions for greenhouse environment. To achieve accurate medium- and long-term predictions of greenhouse temperature and humidity, this study proposes a fuzzy adaptive normalized encoding and decoding network. Initially, a fuzzy preprocessing method is applied to temperature, humidity, and weather prediction data from the Internet of Things, reducing the impact of volatile fluctuations on prediction accuracy. Additionally, a fusion of the fuzzy module with an adaptive normalization technique is introduced to prevent issues like neural saturation and gradient vanishing in deep networks. The framework integrates a Codec model with the adaptive normalization module, incorporating attention normalization to enhance long-term data dependencies and improve predictive performance. The experimental dataset includes hourly temperature and humidity readings collected throughout 2020 from a smart greenhouse in Weifang, Shandong, China, which serves as the training data. Evaluation conducted on data from January 1 to February 15, 2021, shows that the proposed model outperformed all comparative approaches, particularly excelling in long-term greenhouse environment predictions. In terms of RMSE, the AN-FSANC model improved temperature prediction accuracy by 30.8 %, 24.6 %, 29.6 %, 35.3 %, 35.1 %, 16.7 %, 25.3 %, and 24.9 % compared to LSTM, GRU, BiLSTM, BiGRU, Attention-LSTM, Attention-GRU, SAN+LSTM, and AN-SANC, respectively. The model also achieved the highest performance in temperature and humidity predictions, as demonstrated by R2 and MAPE metrics, providing valuable support for agricultural applications. [ABSTRACT FROM AUTHOR]

In a video call there are several components, such as IP phone or softphone, CODEC, and server. Selection of softphone and CODEC is a consideration in building a video communication network because it will affect the quality of video call. This research compare the quality of video calls based on softphone application and CODEC combination. The quality measured by QoS, PSNR, and MOS parameters. Softphone applications examined in this research are Blink, Zoiper, MicroSIP, PortGo, Linphone, and X-Lite. CODEC examined in this research are H.264, VP8, H.263+, and H.263. Each softphone application will be combined with a CODEC that is native to the softphone. There are nine combinations of softphone application and CODEC. Based on the research results, CODEC H.264 has the best performance when paired with the Blink softphone application. CODEC VP8 has the best performance when paired with the Zoiper softphone application. The H.263+ CODEC has the best performance when paired with the PortGo softphone application. The H.263 CODEC and X-Lite softphone applications have the worst test results but still get “good” grades when tested using QoS, PSNR, and MOS parameters.

Adaptive streaming over HTTP is the dominant video streaming technology for more than a decade. HTTP Adaptive Streaming (HAS) systems provide a framework which enables clients to adapt quality with respect to network fluctuations during streaming, hence to optimize the perceived quality on the client side. Recently, network assistance is integrated with HAS in order to improve underlying network conditions and to provide network-related information to the clients. The performance of HAS systems can be further enhanced if the characteristics of the streamed video are considered. In this paper, we propose a HAS system architecture where Software Defined Networking (SDN) technology is utilized for assisting clients to select the most appropriate video codec and bitrate under the constraint of current network conditions as well as routing the video packet over the appropriate paths. In the proposed architecture, layered video is used, where each additional layer improves the quality. The controller estimates the packet loss probability by taking video codec characteristics, the bitrates of the layers and network capacity into account. Based on these estimations, the controller selects the appropriate codec type and video quality for the clients and manage the network. Simulation results show that the performance of the video streaming architecture can be improved significantly when codec, quality and path selection are jointly considered, and combined with SDN flexibility and advantageous.

In order to improve efficiency of coal mine equipment management, a coal mine equipment information management method based on Data Matrix code was proposed. The method includes Data Matrix code generation and Data Matrix code recognition. Address of server that stores equipment operation information is encoded with equipment inherent information, so as to generate Data Matrix code of coal mine equipment information. Image of Data Matrix code on coal mine equipment is collected through intelligent mobile terminal. After the image is preprocessed by graying, median filtering, binarization and Canny edge detection, the improved Hough transform is used to detect L -shaped line of Data Matrix code, and tilt correction operation is carried out, so as to accurately locate coordinate position of Data Matrix code. Then equipment information contained in Data Matrix code is identified by decoding. The method can accurately record and identify equipment information and improve equipment management efficiency.

The usage of internet protocol for voice communication is widely used and more efficient rather than an analog signal. However, there is no security guaranteed on IP-based voice communication. The voice payload can be easily tapped or even manipulated. In the case of improving the security aspect, communication quality should be also considered. VoIP requires sufficient bandwidth to get proper communication quality. The ITU-T released a standard unit of communication quality, known as Mean Opinion Score (MOS) which is made from the subjective judgments of some individuals. However, MOS method takes time and is expensive. In this research, we measure VoIP communication which is secured by using VPN and build a tool for analyzing the voice packet between communication peers. The tool has capabilities to measure delay, jitter, and packet loss. Since VoIP has a QoS standard by ITU-T, the usage of VPN for security purpose needs to be considered. The sound quality might be decreased due to the addition of header for tunneling method, as well as the additional delay when the encryption processing is carried out. We used 3 types of codec: a-Law, GSM, and iLBC which will be passed on 4 types of bandwidth (256, 128, 64, 32 kbps) through the UDP-based VPN that use 3 types of encryption method (3-DES, Blowfish, AES).

Purpose - The article deals with approaches of memory institutions to selection of the format for long term and midterm preservation of video. The goal is to present to reader the process of such decision making and factors that influence it. Design/Methodology/Approach - The Article compares recommendation of authoritative memory institutions, approach of local institutions and institutions specializing in film. Results - Following the analysis of format evaluations, recommendations and format policies of select institutions, we concluded that memory institutions preserve digitized analog video in uncompressed or lossless compressed form. Mostly used formats (combinations of codec and container) are JPEG2000/MXF and FFV1/MKV, while the later seems to us as more advantageous for preservation content from digitization of VHS cassettes. Contrary to that, content that those institutions received as lossy, or originated as such is preserved in native format. Originality/Value - The Article presents summary of suitable format selection in memory institutions with respect to archiving of video. [ABSTRACT FROM AUTHOR]

Aims: Restrictions during the COVID‐19 crisis will have impacted on opportunities to be active. We aimed to (a) quantify the impact of COVID‐19 restrictions on accelerometer‐assessed physical activity and sleep in people with type 2 diabetes and (b) identify predictors of physical activity during COVID‐19 restrictions. Methods: Participants were from the UK Chronotype of Patients with type 2 diabetes and Effect on Glycaemic Control (CODEC) observational study. Participants wore an accelerometer on their wrist for 8 days before and during COVID‐19 restrictions. Accelerometer outcomes included the following: overall physical activity, moderate‐to‐vigorous physical activity (MVPA), time spent inactive, days/week with ≥30‐minute continuous MVPA and sleep. Predictors of change in physical activity taken pre‐COVID included the following: age, sex, ethnicity, body mass index (BMI), socio‐economic status and medical history. Results: In all, 165 participants (age (mean±S.D = 64.2 ± 8.3 years, BMI=31.4 ± 5.4 kg/m2, 45% women) were included. During restrictions, overall physical activity was lower by 1.7 mg (~800 steps/day) and inactive time 21.9 minutes/day higher, but time in MVPA and sleep did not statistically significantly change. In contrast, the percentage of people with ≥1 day/week with ≥30‐minute continuous MVPA was higher (34% cf. 24%). Consistent predictors of lower physical activity and/or higher inactive time were higher BMI and/or being a woman. Being older and/or from ethnic minorities groups was associated with higher inactive time. Conclusions: Overall physical activity, but not MVPA, was lower in adults with type 2 diabetes during COVID‐19 restrictions. Women and individuals who were heavier, older, inactive and/or from ethnic minority groups were most at risk of lower physical activity during restrictions. [ABSTRACT FROM AUTHOR]

Aiming at the problem that it is difficult for traffic monitoring videos to detect multi-scale vehicle targets, especially small vehicle targets in complex scenarios, a codec-based vehicle detection algorithm is proposed. This algorithm is based on YOLOv3. In order to solve the multi-scale vehicle target detection problem, a new multi-level feature pyramid structure added with the codec module to detect vehicle targets of different scales. The experimental results on the KITTI dataset and UA-DETRAC dataset confirm that the algorithm in this paper has achieved good detection results for vehicle targets in various environments and at various scales in the surveillance video, especially for small vehicle targets, which can better meet the actual application demand.

This article seeks to define Digital Theology, first by exploring the development of the CODEC Research Centre at Durham University – perhaps the only centre developed to explore Digital Theology. The aims of the centre and some of its projects are explored leading to a discussion of CODEC’s place within Digital Humanities. The article concludes with a focus on different aspects and definitions of Digital Theology.

Joint Photographic Experts Group (JPEG) XS is a new International Standard from the JPEG Committee (formally known as ISO/International Electrotechnical Commission (IEC) JTC1/SC29/WG1). It defines an interoperable, visually lossless low-latency lightweight image coding that can be used for mezzanine compression within any AV market. Among the targeted use cases, one can cite video transport over professional video links (serial digital interface (SDI), internet protocol (IP), and Ethernet), real-time video storage, memory buffers, omnidirectional video capture and rendering, and sensor compression (for example, in cameras and the automotive industry). The core coding system is composed of an optional color transform, a wavelet transform, and a novel entropy encoder, processing groups of coefficients by coding their magnitude level and packing the magnitude refinement. Such a design allows for visually transparent quality at moderate compression ratios, scalable end-to-end latency that ranges from less than one line to a maximum of 32 lines of the image, and a low-complexity real-time implementation in application-specific integrated circuit (ASIC), field-programmable gate array (FPGA), central processing unit (CPU), and graphics processing unit (GPU). This article details the key features of this new standard and the profiles and formats that have been defined so far for the various applications. It also gives a technical description of the core coding system. Finally, the latest performance evaluation results of recent implementations of the standard are presented, followed by the current status of the ongoing standardization process and future milestones. [ABSTRACT FROM AUTHOR]

This work describes the log-MAP (BCJR) algorithm implementation of a close to capacity dirty paper coding CODEC. The CODEC consists of eight deep pipeline processors. It decodes blocks of 975 bits in 26.9 ms using less than 9.7% of low-cost FPGA (and no DSP blocks). Two pipelines, for alpha and beta, calculate the values of gamma (of the BCJR) to reduce the storage requirements. The final log-likelihood ratio (LLR) is calculated together with alpha, reusing intermediate results. The number of bits used by the different signals of the processor is easily configurable. It was set to six bits to the channel measure signals and eight bits to log of probability signals like alpha, beta, and others. The CODEC clock was 100 MHz. The achieved bit rate is 36.2 Kbps per CODEC, but multiple CODECs can be fit into a single chip. The CODEC is 3.49 dB from the channel capacity. [ABSTRACT FROM AUTHOR]

In view of the requirement of high-speed transmission of payload data in space application, a design scheme of SpaceWire interface controller is proposed according to the SpaceWire protocol. The logic is designed by Verilog programming language, and the interface controller IP is implemented. The prototype is verified by XC4VSX55 FPGA, and the feasibility of the whole design is verified. The IP is implemented in the ASIC LoongSon 1E300. The testing environment is setup, and the synchronization and accuracy of the data transmission process is verified. The actual test results of the ASIC show that the interface′s signaling rates can reach 200 Mb/s, which satisfies the functions stipulated by the protocol.