CORDIC algorithm and it’s applications in DSP

OBJECTIVE: The digital signal processing landscape has long been dominated by the microprocessors with enhancements such as single cycle multiply-accumulate instructions and special addressing modes. While these processors are low cost and offer extreme flexibility, they are often not fast enough for truly demanding DSP tasks. The advent of reconfigurable logic computers permits the higher speeds of dedicated hardware solutions at costs that are competitive with the traditional software approach. Unfortunately algorithms optimized for these microprocessors based systems do not map well into hardware. While hardware efficient solutions often exist, the dominance of the software systems has kept these solutions out of the spotlight. Among these hardware- efficient algorithms is a class of iterative solutions for trigonometric and other transcendental functions that use only shifts and adds to perform. The trigonometric functions are based on vector rotations, while other functions such as square root are implemented using an incremental expression of the desired function. The trigonometric algorithm is called CORDIC an acronym for Coordinate Rotation Digital Computer. The incremental functions are performed with a very simple extension to the hardware architecture and while not CORDIC in the strict sense, are often included because of the close similarity. The CORDIC algorithms generally produce one additional bit of accuracy for each iteration. DESCRIPTION: A detailed study on various modes of CORDIC algorithm is done. First of all a study is made how the CORDIC algorithm is derived from the general vector equation. Then a study is done regarding the various modes of the CORDIC algorithm and how it can be used to find the sine, cosine, tan and logarithm functions, its use in conversion of coordinate systems. An attempt is made to carry out a rigorous study of its use in DSP oriented applications AND how it has revolutionized the DSP scenario. Finally simulations are carried out using MATLAB to support the purpose of our study. RESULTS The results clearly bring out the advantage of using CORDIC algorithm. First of all the sine and cosine of any angle could be found out easily. Similar is the case of logarithm and hyperbolic functions. The simulation results prove the fact that the hardware complexity gets reduced by using the CORDIC algorithm. A large no of plots were obtained for different 7 functions. Finally the implementation in DCT was carried out and the results obtained were in line with those of the theoretical values. CONCLUSION The CORDIC algorithms presented in this paper are well known in the research and super computing circles. Here the basic CORDIC algorithm and a partial list of potential applications of potential applications of a CORDIC based processor array to digital signal processing is presented. The CORDIC based DCT architecture for low power design has been proposed. The proposed multiplierless CORDIC based DCT architecture produces high throughput and is easy to implementing VLSI. The proposed architecture reduced the input data range for the CORDIC processor by split and the no of compensation iterations in CORDIC based DCT computation by utilizing that most images have similar neighboring pixels. The project also shows that a tool is available for use in FPGA based computing machines, which are the likely basis for the next generation DSP systems

Relay based traffic contol system using infrared pair detectors

A relay is an electromechanical device that is actuated by an electrical current. The small current flowing in relay circuit causes the opening or closing of high power requiring circuit. The proposed traffic control system in this project will be a simple relay based controller system which can adapt according to the amount of traffic in one direction. The relay will require only small amount of current for its operation but will be used to operate high power requiring traffic lights. Also relay switching will be used to operate more number of components with the same port. The system will require relay board, microcontroller and IR sensor for its implementation. In every direction the road will consist of an IR transmitterreceiver pair at a certain distance from traffic lights. When the traffic will become heavy in one particular direction during emergency situations it will increase the time duration for that particular road thus will help in getting rid off from the heavy traffic congestion which would not have been possible if the timing sequence of the system has been kept fixed

Automatic Detection of Oral Squamous Cell Carcinoma from Histopathological Images of Oral Mucosa Using Deep Convolutional Neural Network

Worldwide, oral cancer is the sixth most common type of cancer. India is in 2nd position, with the highest number of oral cancer patients. To the population of oral cancer patients, India contributes to almost one-third of the total count. Among several types of oral cancer, the most common and dominant one is oral squamous cell carcinoma (OSCC). The major reason for oral cancer is tobacco consumption, excessive alcohol consumption, unhygienic mouth condition, betel quid eating, viral infection (namely human papillomavirus), etc. The early detection of oral cancer type OSCC, in its preliminary stage, gives more chances for better treatment and proper therapy. In this paper, author proposes a convolutional neural network model, for the automatic and early detection of OSCC, and for experimental purposes, histopathological oral cancer images are considered. The proposed model is compared and analyzed with state-of-the-art deep learning models like VGG16, VGG19, Alexnet, ResNet50, ResNet101, Mobile Net and Inception Net. The proposed model achieved a cross-validation accuracy of 97.82%, which indicates the suitability of the proposed approach for the automatic classification of oral cancer data

A Data Aggregation Approach Exploiting Spatial and Temporal Correlation among Sensor Data in Wireless Sensor Networks

Wireless sensor networks (WSNs) have various applications which include zone surveillance, environmental monitoring, event tracking where the operation mode is long term. WSNs are characterized by low-powered and battery-operated sensor devices with a finite source of energy. Due to the dense deployment of these devices practically it is impossible to replace the batteries. The finite source of energy should be utilized in a meaningful way to maximize the overall network lifetime. In the space domain, there is a high correlation among sensor surveillance constituting the large volume of the sensor network topology. Each consecutive observation constitutes the temporal correlation depending on the physical phenomenon nature of the sensor nodes. These spatio-temporal correlations can be efficiently utilized in order to enhance the maximum savings in energy uses. In this paper, we have proposed a Spatial and Temporal Correlation-based Data Redundancy Reduction (STCDRR) protocol which eliminates redundancy at the source level and aggregator level. The estimated performance score of proposed algorithms is approximately 7.2 when the score of existing algorithms such as the KAB (K-means algorithm based on the ANOVA model and Bartlett test) and ED (Euclidian distance) are 5.2, 0.5, respectively. It reflects that the STCDRR protocol can achieve a higher data compression rate, lower false-negative rate, lower false-positive rate. These results are valid for numeric data collected from a real data set. This experiment does not consider non-numeric values

A Data Aggregation Approach Exploiting Spatial and Temporal Correlation among Sensor Data in Wireless Sensor Networks

Wireless sensor networks (WSNs) have various applications which include zone surveillance, environmental monitoring, event tracking where the operation mode is long term. WSNs are characterized by low-powered and battery-operated sensor devices with a finite source of energy. Due to the dense deployment of these devices practically it is impossible to replace the batteries. The finite source of energy should be utilized in a meaningful way to maximize the overall network lifetime. In the space domain, there is a high correlation among sensor surveillance constituting the large volume of the sensor network topology. Each consecutive observation constitutes the temporal correlation depending on the physical phenomenon nature of the sensor nodes. These spatio-temporal correlations can be efficiently utilized in order to enhance the maximum savings in energy uses. In this paper, we have proposed a Spatial and Temporal Correlation-based Data Redundancy Reduction (STCDRR) protocol which eliminates redundancy at the source level and aggregator level. The estimated performance score of proposed algorithms is approximately 7.2 when the score of existing algorithms such as the KAB (K-means algorithm based on the ANOVA model and Bartlett test) and ED (Euclidian distance) are 5.2, 0.5, respectively. It reflects that the STCDRR protocol can achieve a higher data compression rate, lower false-negative rate, lower false-positive rate. These results are valid for numeric data collected from a real data set. This experiment does not consider non-numeric values