Vectoring: meaning, definitions and examples
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vectoring
[ ˈvɛktərɪŋ ]
mathematics, physics
Vectoring refers to a process used in various mathematical and engineering contexts, primarily in the fields of physics and computer graphics. It involves the representation and manipulation of vectors, which are quantities that have both magnitude and direction. In mathematics, vectoring can also pertain to the transformation of data points into a vector space, which allows for easier analysis and computation. Vectoring is essential in algorithms for data processing, machine learning, and spatial analysis.
Synonyms
directional representation, mapping, vectorization.
Examples of usage
- Vectoring allows for high-speed data processing.
- In physics, vectoring helps in understanding forces acting on an object.
- The concept of vectoring is fundamental in computer graphics.
- Advanced vectoring techniques are used in modern robotics.
Translations
Translations of the word "vectoring" in other languages:
🇵🇹 vetorização
🇮🇳 वेक्टरिंग
🇩🇪 Vektorisierung
🇮🇩 vektorisasi
🇺🇦 векторизація
- векторизація даних
- векторизувати
🇵🇱 wektoryzacja
🇯🇵 ベクトル化
🇫🇷 vectorisation
🇪🇸 vectorización
🇹🇷 vektörleme
🇰🇷 벡터화
🇸🇦 تحويل إلى متجهات
🇨🇿 vektorování
🇸🇰 vektorovanie
🇨🇳 向量化
🇸🇮 vektoriranje
🇮🇸 vettvang
🇰🇿 векторизация
🇬🇪 ვექტორიზაცია
🇦🇿 vektorlaşdırma
🇲🇽 vectorización
Etymology
The term 'vector' originates from the Latin word 'vector', which means 'to carry' or 'to bring.' This roots back to the early mathematical concepts developed in the 17th century, when scientists and mathematicians began exploring the properties of quantities that could be represented in terms of their magnitude and direction. The formalization of vectors was significantly advanced in the 19th century with the work of mathematicians such as William Rowan Hamilton, who introduced quaternions, and Josiah Willard Gibbs, who contributed to vector algebra. Over time, the application of vectoring expanded into various fields, including physics, engineering, and computer science, where it is crucial for understanding and visualizing multi-dimensional data. Today, vectoring has become a fundamental aspect of numerous applications, including graphics rendering, data analysis, and artificial intelligence, highlighting its importance in both theoretical and practical contexts.