{"title":"Novel CAD Design Methodology for Two Stage Opamp with Noise-Power Balance","authors":"B. K. Mishra, Sandhya Save","doi":"10.1109/ICSAP.2010.44","DOIUrl":"https://doi.org/10.1109/ICSAP.2010.44","url":null,"abstract":"In recent years, there have been great advancements in the speed, power, and complexity of integrated circuits, such as application specific integrated circuit (ASIC) chips. Advances in integrated circuit technology have led to the birth and proliferation of a wide variety of integrated circuits, including but not limited to application specific integrated circuits, microcontrollers, digital signal processors, general purpose microprocessors, and network processors. ASIC (application specific integrated circuit) technology has evolved from a chip-set philosophy to an embedded core based system-on-a-chip (SoC) i.e. analog and mixed signal chip (AMS)concept. Many applications such as communication devices (VoIP, MoIP, wireless) require chip speeds that may be unattainable with separate IC products. Considering different design constraints, 90% of time is consumed while designing analog block rather than digital block due unavailability of standard analog design tool, also the largest problem is the design constraints of analog circuits are sometimes implicit, which makes porting the design to a new environment difficult and prone to failure. Creating portable analog modules requires the system to capture not only the sized schematic of the circuit but also the objectives that circuit is trying to achieved. This paper applies the embedding knowledge into pure simulation based methodology to perform automatic analog intergraded circuit design, synthesis and optimization in order to reduce development time of this kind of circuits. A practical platform independent computer aided design methodology for synthesis of (analog circuits) Operational Amplifier with flexible noise –power balance is presented in this paper. In order to evaluate the fitness of the circuit specifications in any iteration of SA, NGSPICE simulation is used. The simulation results confirm the efficiency of presented methodology in determining the device sizes in analog circuits.","PeriodicalId":303366,"journal":{"name":"2010 International Conference on Signal Acquisition and Processing","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134370652","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Improved Particle Swarm Optimization for Dual-Channel Speech Enhancement","authors":"Laleh Badri Asl, Vahid Majid Nezhad","doi":"10.1109/ICSAP.2010.30","DOIUrl":"https://doi.org/10.1109/ICSAP.2010.30","url":null,"abstract":"This paper, proposes an improved particle swarm optimization algorithm for speech enhancement. In the proposed algorithm, the population is divided into two subgroups. One of the subgroups searches the space globally, whereas the other one explores the problem space locally. The proposed algorithm surpasses the standard PSO, by stimulating the inactive particles and local search around the global best. Experimental results indicate that improved particle swarm optimization (IPSO) outperforms the standard particle swarm optimization (SPSO), and gradient-based NLMS algorithm in dual-channel speech enhancement applications.","PeriodicalId":303366,"journal":{"name":"2010 International Conference on Signal Acquisition and Processing","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132642536","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"DSP Course Teaching Using Moodle","authors":"V. Dharmadhikari, D. Y. Loni","doi":"10.1109/ICSAP.2010.11","DOIUrl":"https://doi.org/10.1109/ICSAP.2010.11","url":null,"abstract":"Advances in the multimedia technology provide an opportunity to enhance learning an Engineering subject like Digital Signal Processing (DSP). The paper presents a new teaching method that effectively integrates Information Technology into teaching - learning process. The entire DSP modules are implemented in an open source Course Management System (CMS), Moodle. It helps the students at undergraduate level in learning introductory DSP and experimenting with its basic concepts. At the same time, course instructors also find smooth flow of the contents covered that helps them in enhancing the effectiveness of their lectures, assign tasks to students with simple methods of evaluation and easy tracking of student’s progress at every stage of learning. Moodle has been adopted by many people and organizations around the world, as it offers a tightly integrated set of tools to develop a powerful E-Learning tool. The focus here is upon effective adoption of the tool so that the teacher concentrates more on the learning activities and uses all the Moodle tools successfully. Moodle helps to present the course contents exactly the way the teacher has mapped the subject structure, but through a more controlled environment. The method is well suited for teaching the theoretical and mathematical concepts of DSP.","PeriodicalId":303366,"journal":{"name":"2010 International Conference on Signal Acquisition and Processing","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123824853","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Segmentation Algorithm for Multiple Face Detection for Color Images with Skin Tone Regions","authors":"H. Lakshmi, S. Patilkulkarni","doi":"10.1109/ICSAP.2010.42","DOIUrl":"https://doi.org/10.1109/ICSAP.2010.42","url":null,"abstract":"In this paper, an improved segmentation algorithm for face detection in color images with multiple faces and skin tone regions is proposed. Algorithm ingeniously combines different color space models, specifically, HSI and YCbCr along with Canny and Prewitt edge detection techniques. Improvement over previous approaches by other researchers is demonstrated using example images where segmentation stage is critical for face detection.","PeriodicalId":303366,"journal":{"name":"2010 International Conference on Signal Acquisition and Processing","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122784979","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"An Approach to Distributed Remote Bridges Monitoring Based on Soft Middleware","authors":"Pengfei Shao, Xuan Zhang, Yibo Ge","doi":"10.1109/ICSAP.2010.9","DOIUrl":"https://doi.org/10.1109/ICSAP.2010.9","url":null,"abstract":"It is very important to do real-time bridge’s health monitoring and have a long time continual analysis and evaluation for the field status of the bridge. In order to make bridges monitoring more sufficient and intelligent, and reduce the cost of monitoring and maintenance of the multiple bridges, it is a new way to implement loosely coupled and distributed monitoring for all the bridges in one city or area. But with the fact that each of the present bridge monitoring subsystems adept different monitoring technology and network architecture, it is difficult to directly connect the existing bridge monitoring systems with their different technical interfaces, and will cost expensive to use some kind of hardware devices to achieve system integration. In this paper, we provide a bridges monitoring system which uses industrial soft middleware to provide different technical interfaces for the integration of the different existing bridge monitoring subsystems and build a unified communication platform over the public communication network. In this way, we lead into loosely coupled and distributed remote monitoring of the multiple bridges in one city or area.","PeriodicalId":303366,"journal":{"name":"2010 International Conference on Signal Acquisition and Processing","volume":"91 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123547186","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Enhanced Performance of H.264 Using FPGA Coprocessors in Video Surveillance","authors":"P. Nirmalkumar, E. MuraliKrishnan, E. Gangadharan","doi":"10.1109/ICSAP.2010.31","DOIUrl":"https://doi.org/10.1109/ICSAP.2010.31","url":null,"abstract":"As video and image processing design challenges becoming more complex, FPGA based coprocessors are required to boost overall DSP performance. For a High Definition (HD) video compression standard like H.264/AVC, the computational performance required has outstripped what standalone DSPs can provide. This H.264/AVC standard achieves a significant improvement in coding efficiency at the cost of increased computational complexity and creates a big challenge for efficient hardware and software executions. This paper implements a novel design combining DSP hardware platform with FPGA coprocessor architecture for the H.264/AVC codec in video surveillance environments. The main motivation to go for the FPGA coprocessor approach was the scalability in terms of processing power, cycle count, and better control of logic implementation, high frame rates and enhancement to support HD resolution. A properly architected coprocessor system off-loads a DSP processor and efficiently executes computationally intensive blocks of H.264/AVC like motion estimation, motion compensation modules as part of hardware acceleration in FPGA freeing up more valuable processing power of the DSP system.","PeriodicalId":303366,"journal":{"name":"2010 International Conference on Signal Acquisition and Processing","volume":"549 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131787176","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A Discrete Wavelet Transform Based Approach to Hindi Speech Recognition","authors":"Shivesh Ranjan","doi":"10.1109/ICSAP.2010.21","DOIUrl":"https://doi.org/10.1109/ICSAP.2010.21","url":null,"abstract":"In this paper, we propose a new scheme for recognition of isolated words in Hindi Language speech, based on the Discrete Wavelet Transform. We first compute the Discrete Wavelet Transform coefficients of the speech signal. Then, Linear Predictive Coding Coefficients of the Discrete Wavelet Transform coefficients are calculated. Our scheme then uses K Means Algorithm on the obtained Linear Predictive Coding Coefficients to form a Vector Quantized codebook. Recognition of a spoken Hindi word is carried out by first calculating its Discrete Wavelet Transform Coefficients, followed by Linear Predictive Coding Coefficient calculation of these Discrete Wavelet Transform Coefficients, and then deciding in favor of the Hindi word whose corresponding centroid (in the Vector Quantized codebook) gives a minimum squared Euclidean distance error with respect to the word under test.","PeriodicalId":303366,"journal":{"name":"2010 International Conference on Signal Acquisition and Processing","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132289347","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Hybrid Self Organizing Map for Improved Implementation of Brain MRI Segmentation","authors":"T. Logeswari, M. Karnan","doi":"10.1109/ICSAP.2010.56","DOIUrl":"https://doi.org/10.1109/ICSAP.2010.56","url":null,"abstract":"Image segmentation denotes a process of partitioning an image into distinct regions. A large variety of different segmentation approaches for images have been developed. Among them, the clustering methods have been extensively investigated and used. In this paper, a clustering based approach using a Self Organizing Map (SOM) algorithm is proposed for medical image segmentation. This paper describe segmentation method consists of two phases. In the first phase, the MRI brain image is acquired from patient database. In that film artifact and noise are removed. In the second phase (MR) image segmentation is to accurately identify the principal tissue structures in these image volumes. A new unsupervised MR image segmentation method based on fuzzy C-Mean clustering algorithm for the Segmentation is presented","PeriodicalId":303366,"journal":{"name":"2010 International Conference on Signal Acquisition and Processing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128783168","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Chandan Banerjee, Gaurav Pandey, Hemant Kr. Namdeo
{"title":"Low Pass Filtering and Computing Cost","authors":"Chandan Banerjee, Gaurav Pandey, Hemant Kr. Namdeo","doi":"10.1109/ICSAP.2010.75","DOIUrl":"https://doi.org/10.1109/ICSAP.2010.75","url":null,"abstract":"In this paper we are dealing with a linearly swept-frequency cosine signal so called “chirp” function. We are generating an image row of the same function of required frequency (frequency f = 1 ... around 256 pixel/period, amplitude = 1). After that we are stacking 20 rows to generate a strip image and then we are applying different low pass filters and calculating the attenuation i.e., damping pixel by pixel. On the same time we are calculating computing effort throughout the all processes and comparing all results. We can also analyze iterative convoluted filters, which is more useful than conventional binomial filters.","PeriodicalId":303366,"journal":{"name":"2010 International Conference on Signal Acquisition and Processing","volume":"190 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117348100","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A Fast Motion Estimation Algorithm for H.264","authors":"Xiaomin Wu, Weizhang Xu, Nanhao Zhu, Zhanxin Yang","doi":"10.1109/ICSAP.2010.12","DOIUrl":"https://doi.org/10.1109/ICSAP.2010.12","url":null,"abstract":"Motion Estimation(ME) plays an important role in digital video compression, since it can significantly affect the image accuracy and the compression ratio. Also, motion estimation process is a part of the encoder which is high complex and computation-intensive, therefore it hinders real-time applications of H.264 video compression. To reduce computational complexity and maintain the image quality, an integer pixel fast motion estimation algorithm is proposed in this paper. Combining the characters of the UMHexagonS algorithm and the EPZS algorithm, the proposed algorithm selects various searching patterns according to the motion types of the image and introduces a early-termination algorithm. Experimental results demonstrate that the proposed algorithm has less ME time than FS, UMHexagonS and EPZS algorithm with essentially the same PSNR.","PeriodicalId":303366,"journal":{"name":"2010 International Conference on Signal Acquisition and Processing","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124171825","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}